Embargoed until 11 October 2016 at 11.00 CET
International Land Deals
for Agriculture
Fresh insights from the Land Matrix: Analytical Report II
Kerstin Nolte, Wytske Chamberlain, Markus Giger
International Land Deals for Agriculture
Fresh insights from the Land Matrix: Analytical Report II
Authors: Kerstin Nolte, Wytske Chamberlain, Markus Giger
With contributions from:
Lorraine Ablan (AFA), Afia Afenah, Christof Althoff, Anne Hoss, Martin Ostermeier, Robert J. Pijpers (GIGA), Thomas Breu, Tobias Haller,
Fabian Käser, Franziska Marfurt, Christoph Oberlack, Stephan Rist (University of Bern), Angela Harding (University of Pretoria), Lucas
Seghezzo, Gabriel Seghezzo, Martín Simón, Cristian Venencia (FUNDAPAZ), Hijaba Ykhanbai (Jasil)
We gratefully acknowledge internal reviews by Ward Anseeuw, Silvia Forno, Jann Lay, Annalisa Mauro, Peter Messerli and Saliou Niassy.
We are also grateful for external reviews provided by Fernando Eguren, Harold Liversage, Madiodio Niasse, Aniedi Okure and Roel
R. Ravanera.
Editing: David Wilson
Design/Layout: MediaChef
Publisher: Centre for Development and Environment (CDE), University of Bern; Centre de coopération internationale en recherche
agronomique pour le développement (CIRAD); German Institute of Global and Area Studies (GIGA); University of Pretoria; Bern Open
Publishing (BOP)
© CDE/CIRAD/GIGA/University of Pretoria, 2016
This report is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) Licence. See http://creativecommons.org/
licenses/by/4.0/ to view a copy of the licence.
Citation:
Nolte, Kerstin; Chamberlain, Wytske; Giger, Markus (2016). International Land Deals for Agriculture. Fresh insights from the Land Matrix:
Analytical Report II. Bern, Montpellier, Hamburg, Pretoria: Centre for Development and Environment, University of Bern; Centre de
coopération internationale en recherche agronomique pour le développement; German Institute of Global and Area Studies; University
of Pretoria; Bern Open Publishing.
ISBN: 978-3-906813-27-1 [print]
ISBN: 978-3-906813-28-8 [e-print]
DOI: 10.7892/boris.85304
The e-print version is available at:
www.landmatrix.org
Further acknowledgements
The Land Matrix is partly financed by the internal resources of the partner organisations. The additional support of the BMZ (German
Federal Ministry for Economic Cooperation and Development), the European Commission (administered through Expertise France), the
French Ministry of Foreign Affairs, the Swiss Agency for Cooperation and Development (SDC) and the Swiss National Science Foundation
is greatly appreciated.
Special thanks also go to Christof Althoff and Martin Ostermeier (GIGA) for maintaining the global database and assisting with the data
analysis, as well as to Afia Afenah, Anne Hoss and Siri Völker (GIGA) and Angela Harding and Ikageng Makuleke (University of Pretoria) for
their excellent research assistance; Manuel Abebe (CDE) for geographic information system analysis; Silvia Forno (ILC) for continued and
dedicated support to the Land Matrix Initiative; and Saliou Niassy and Gaia Manco (University of Pretoria) for their support in producing
this report.
Last but not least, the Land Matrix partners wish to express their gratitude to all those members of their networks who have significantly
contributed to data collection.
The support of the BMZ (German Federal Ministry for Economic Cooperation and Development), the European Commission
(administered through Expertise France), the French Ministry of Foreign Affairs, the Swiss Agency for Cooperation and Development
(SDC) and the Swiss National Science Foundation is greatly appreciated.
The LMI Partners and Regional Focal Points are:
TABLE OF CONTENTS
List of figures
ii
List of tables
iii
List of boxes
iii
Acronyms and abbreviations
iv
Foreword
v
Summary
vi
1.
Introduction
1
1.1.
Background and objectives of this report
1
1.2.
The LMI: providing data and supporting more equitable governance of land deal
2
1.3.
Data sources and reliability: making use of the best available data
3
1.4.
Scope of this report
6
2.
Overview and trends in large-scale agricultural land acquisitions
7
2.1.
Overview of all deals
7
2.1.1. Database contains 1,549 deals in total
7
2.1.2. Size of deals
8
2.1.3. Choice of contracts shows a clear regional pattern
9
2.2.
Investment intention: focus on agriculture
10
2.3.
The “rush for land” is moving towards the implementation phase
12
2.4.
Regional trends and top target countries
16
2.4.1. Africa remains the most targeted continent
16
2.4.2. Top target countries
17
2.4.3. Many deals take place in a context of poverty and food insecurity
18
2.4.4. Tenure insecurity as a driver of land acquisitions
20
2.5.
Synthesis
21
3.
The investors: who, where and why?
22
3.1.
Origin of investors
22
3.2.
Strong regional patterns
23
3.3.
Investor types and their networks
24
3.3.1. Private companies
27
3.3.2. Stock exchange-listed companies
28
3.3.3. Investment funds
29
3.3.4. State-owned entities
29
3.3.5. Beyond direct investment
30
3.4.
Intention
30
3.5.
Partnerships with domestic shareholders
32
3.6.
Synthesis
33
4.
What type of land is targeted by land deals?
34
4.1.
Tropical savannah and tropical rainforest are the most targeted climatic zones
34
4.2.
Former land use and land cover
36
4.3.
Socio-ecological contexts of acquired land
37
4.4.
Synthesis
38
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International Land Deals for Agriculture
5.
Impacts of large-scale agricultural land acquisitions
39
5.1.
Acquisition of land: little consultation and frequent rejection of deals by communities
40
5.2.
Start-up phase: temporary employment creation and infrastructure development
43
5.3.
Operational projects: socio-economic and ecological implications
44
5.3.1. Development of social and community infrastructure
46
5.3.2. Employment generation
46
5.3.3. Access to agricultural markets and spillovers
48
5.3.4. Environmental effects
49
Synthesis
51
5.4.
References
52
List of Figures
Figure 1: All sources in the Land Matrix
3
Figure 2: Number of sources per deal (multiple entries)
4
Figure 3: Data overview
7
Figure 4: Agricultural intentions of land acquisition by percentage of area
10
Figure 5: Crops cultivated (% of area)
11
Figure 6: Leading crops according to area under contract
12
Figure 7: Transnational agricultural deals with a concluded contract, 2000–2016
13
Figure 8: Development of land size under contract and size under operation
15
Figure 9: Years needed for projects to move to production phase
16
Figure 10: Global heat map of land deals contained in the Land Matrix
17
Figure 11: Top 20 target countries according to size of concluded deals
(showing different implementation statuses)
18
Figure 12: Typology of land acquisitions according to the Global Hunger Index 2015 and agricultural GDP
19
Figure 13: Typology of land acquisitions: land tenure insecurity and agricultural GDP
21
Figure 14: Top 20 investor countries for concluded deals with agricultural intention
22
Figure 15: Geographical investment patterns by investor region for area under contract
24
Figure 16: Example of a multi-layered investment chain
26
Figure 17: Regional trends of concluded deals by investment funds
29
Figure 18: Intentions of top 10 investor countries
31
Figure 19: Intention of agricultural deals by investor type
31
Figure 20: Share of land acquisitions in different Köppen–Geiger climate classes in target countries
34
Figure 21: West and Central Africa: Spatial distribution according to climate zones of land deals contained
in the Land Matrix
35
Figure 22: East Africa: Spatial distribution according to climate zones of land deals contained in the
Land Matrix
35
Figure 23: Primary land cover types targeted by land deals
36
Figure 24: Former land ownership (% of area)
40
Figure 25: Community consultation
41
Figure 26: Status of compensation offered
42
Figure 27: Community benefits
46
Figure 28: Labour intensities in the Land Matrix
47
Figure 29: Regional distribution of contract farming
48
Figure 30: Sources of water extraction
50
International Land Deals for Agriculture
» ii
List of Tables
Table 1: All international land acquisitions recorded in the Land Matrix database
7
Table 2: Intended size of deals according to different negotiation statuses
8
Table 3: Number of concluded deals according to contract size
9
Table 4: Nature of deals, by continent
9
Table 5: Intention of land acquisitions
10
Table 6: Agricultural intentions across regions (% of area)
11
Table 7: Implementation status of agricultural deals
14
Table 8: Transition from first reported implementation status to current implementation status
15
Table 9: Continental breakdown of target regions for agricultural deals
16
Table 10: Top 10 investor countries for contracts concluded in 2000–2011 and 2012–2016
23
Table 11: Land acquisitions by investor type
26
Table 12: Land acquisitions by investor type and target region
27
Table 13: Shared equity with domestic investor by target region
32
Table 14: Investor types engaged with domestic partner
32
Table 15: Domestic shareholders by investor type
33
Table 16: Intention of deals with domestic stakeholders
33
Table 17: Regional distribution of former land use
37
List of Boxes
Box 1: How does this report differ from the 2012 Analytical Report?
1
Box 2: The pitfalls of data collection – reflections from Sierra Leone
5
Box 3: Size variables and conflicting information on the size of deals
8
Box 4: Large-scale projects forced to scale down by target governments
13
Box 5: Eastern Europe – a special history in the development of land ownership
20
Box 6: Chinese investment in African agriculture
25
Box 7: The ABCD group in Latin America
27
Box 8: South-East Asian dominance and expansion of oil palm plantations
28
Box 9: Meta-analysis reveals patterns of livelihood impacts
39
Box 10: Resistance to land deals – the case of Senhuile in Senegal
43
Box 11: Setting up a farm – Dominion Farms Ltd in Kenya
43
Box 12: Bioenergy project fails to deliver promised benefits
44
Box 13: Rice project falls short of development potential
45
Box 14: Mitigating the impacts of mining operations
45
Box 15: Large-scale land acquisitions – employment generators or job killers?
47
Box 16: Outgrower schemes in Zambia
49
Box 17: Environmental concerns and silvopastoral systems in Salta, Argentina
49
Box 18: Effects of land acquisitions on water resources
51
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International Land Deals for Agriculture
Acronyms and Abbreviations
ADM
Archer Daniels Midland
AFA
Asian Farmers’ Association for Sustainable Rural Development
AU
African Union
BMBF
German Federal Ministry of Education and Research
BMZ
German Federal Ministry for Economic Cooperation and Development
CDE
Centre for Development and Environment
CFS
Committee on World Food Security
CIRAD
Centre de Coopération Internationale en Recherche Agronomique pour le Développement
CSO
Civil society organisation
CSR
Corporate social responsibility
EC
European Commission
EU
European Union
FAO
Food and Agriculture Organization of the United Nations
FPIC
Free, prior and informed consent
FUNDAPAZ
Fundación para el Desarrollo en Justicia y Paz
GDP
Gross domestic product
GHI
Global Hunger Index
GIGA
German Institute of Global and Area Studies
GIS
Geographic information system
GIZ
Deutsche Gesellschaft für Internationale Zusammenarbeit
ICC
Indicative Crop Classification (FAO)
ILC
International Land Coalition
LM
Land Matrix
LMI
Land Matrix Initiative
MoU
Memorandum of understanding
NGO
Non-governmental organisation
RSB
Roundtable on Sustainable Biomaterials
SDC
Swiss Agency for Cooperation and Development
SDGs
Sustainable Development Goals
UNCTAD
United Nations Conference on Trade and Development
VRG
Vietnam Rubber Group
WWF
World Wide Fund for Nature
International Land Deals for Agriculture
» iv
Foreword
The beta version of the Global Observatory was launched by
the Land Matrix in April 2012 with the aim of creating a reliable
source of data to feed debate and provoke informed action on
large-scale land deals. The Land Matrix has since become an
important reference point and its website has received over
165,000 visits since 2013, with the database being downloaded
20,000 times. It is widely quoted in research papers and in the
press, and is increasingly being used by national organisations –
including those representing land users themselves – to inform
strategic planning and to open up policy dialogue.
The Sustainable Development Goals have renewed the demand
for good data that can inform action and measure progress
towards their achievement. The Land Matrix is a contribution
to this effort, producing a wealth of data to complement official
statistics and geographical information on land deals and their
impacts.
Transparency is embraced by the International Land Coalition
(ILC)’s 207 members as one of the 10 critical ingredients
in achieving “people-centred land governance” – i.e. land
governance that first and foremost meets the needs, and
responds to the priorities, of the women, men and communities
who live off the land.
We are beginning to observe private and governmental investors
becoming more open to sharing their investment projects,
Annalisa Mauro
International Land Coalition
v »
International Land Deals for Agriculture
realising that it is in their interests to do so. Nevertheless,
transparency is still not the norm, and there remains a challenge
in complementing global data with local data, particularly
regarding the impact of land deals.
This report is being launched in the same year that over 400
organisations have come together behind a Global Call to Action
on Community and Indigenous Land Rights, drawing attention to
the massive gap between the area of land globally that is claimed
by the world’s indigenous peoples and local communities (65%)
and the proportion of these claims that are actually recognised
by governments (10%) – which means that the livelihoods of up to
2.5 billion women and men worldwide are rendered precarious.
This is land where the utmost caution must be exercised in
considering any form of large-scale land-based investment. The
authors of this report find that about one-third of agricultural
deals recorded in the Land Matrix involve land formerly used
by smallholder farmers. This gap in recognition, which is fuelling
large-scale dispossessions, is one of the key issues on which
urgent joint action is needed.
ILC is glad that the Land Matrix Initiative is becoming more
and more relevant as a data source for communities, activists,
indigenous peoples, researchers, governments and the private
sector alike to make informed decisions on global and local land
governance.
Summary
Land acquisitions continue to be an
important trend
Large-scale land acquisitions continue to be an important
issue for governments, development organisations, NGOs and
farmers’ organisations all over the world; this remains the case
even in times of global economic slowdown, recession and
crisis. The scale of this trend and its significant impacts on rural
transformation and livelihoods make it necessary to further
monitor, observe and positively influence such deals wherever
possible.
The Land Matrix Initiative (LMI) is a global partnership which aims
to improve transparency around large-scale land acquisitions. It
collects and provides data and information through a network
of global and regional partners. In April 2012 it published its
first Analytical Report (Anseeuw et al., 2012), which provided a
comprehensive overview of the phenomenon, which at that time
was newly emerging.
A new and updated report is needed
Since the 2012 report, large-scale land acquisitions have
continued to take place and further insight has been obtained.
Over this period the LMI has undergone a number of changes:
it has incorporated regional partners in the global South; the
database and platform have undergone major developments
which enable it to present continuously updated information,
with individual deals being tracked over time; and data gathering
has been improved, drawing on multiple source types for each
deal. While our understanding of large-scale land acquisitions
is increasing, levels of transparency remain low. Hence the
motivation of the LMI to support informed, equitable decisionmaking remains relevant.
This report aims to contribute to the body of knowledge available
on land acquisitions in low- and middle-income countries by
presenting an up-to-date analysis of the data contained in the
Land Matrix database and providing complementary evidence
based on case studies. It provides a concise overview of general
trends and developments, as well as regional and local insights.
In particular, the report gives an update on recent developments,
zooms in to focus on the key target regions, investigates who
acquires land and discusses emerging evidence on the impacts
of large-scale land acquisitions. Additionally, through a number
of case studies provided by our network partners, it provides
insights into realities on the ground.
Focus on international land acquisitions for
agriculture
The scope of this report is limited to large-scale transnational
deals in the agricultural sector, as this is where the Land Matrix
can claim to identify global trends. The Land Matrix and its
partners are clearly aware of the importance of domestic deals,
however, and this data gap will be partly overcome by the
establishment of local observatories in the near future.
Deals in sectors such as mining, forestry and energy are equally
central to the impact of and debate around land acquisitions. A
short overview of deals for non-agricultural purposes is included
in this report.
Data limitations
Although data collection by the LMI is unlikely to result in a
complete inventory of all large-scale land acquisitions worldwide,
the data provides a sample that is large and representative
enough for empirical analysis. Data limitations mean that
aggregate figures should be interpreted with care. Earlier
estimates of global land acquisitions, as published in our previous
report, were often higher because they included intended deals
that were subsequently downsized or failed to materialise. This
is why the Land Matrix data now explicitly captures the dynamics
of land deals. We trace deals from their initial announcement
through the negotiation process, conclusion of contract and
implementation, and also their potential failure.
Agricultural land acquisitions are
increasingly becoming operational
Overall, the Land Matrix has captured 1,204 concluded deals (for
all intentions), which cover over 42.2 million hectares of land.
Intended deals target 20 million hectares and failed deals 7.2
million hectares. Overall, concluded deals are smaller in size
than their original intention and the average size is smaller than
intended and failed projects. The large majority of deals are
for farming purposes: there are 1,004 concluded large-scale
agricultural land acquisitions covering 26.7 million hectares
under contract.
For about 70% of these agricultural land acquisitions activities
have started, and most of these are in operation. In the 2012
Analytical Report only 323 deals had seen operations begin,
but this number has nearly doubled to 604 and the area under
production has increased from 1.7 million hectares to 6.4 million
hectares. Implementation is typically quite fast: most deals enter
the production phase in less than three years.
Food crops dominate
Food crops continue to play the major role, both in terms of
number of deals (553) and area (9.2 million hectares), followed
by unspecified agricultural intentions – mostly involving oil palm
(263 deals on 5.6 million hectares) and agrofuels (221 deals on
5.1 million hectares). The crops planted most often are oil seeds,
including oil palm and jatropha, cereals such as corn and wheat,
and sugar crops. Most of these crops can also be used for fuel
or renewable energy, and this is captured in the database where
applicable.
Africa is the most targeted continent, but
the main target countries are elsewhere
Africa remains the most significant target area, with deals
concluded in many countries across the continent. It accounts
for 422 concluded agricultural deals (42% of all deals) and 10
International Land Deals for Agriculture
» vi
million hectares (37%). It also has the highest number of intended
deals (147 deals; 13.2 million hectares). Land acquisitions are
concentrated along major rivers and in East Africa. The second
most important region is Eastern Europe, which accounts for 96
deals and 5.1 million hectares of concluded deals.
The top five individual target countries (Indonesia, Ukraine,
Russia, Papua New Guinea and Brazil) account for 46% of the
total area of all concluded agricultural deals and 25% in terms of
the number of deals.
Large diversity in origin of investors
The top five investor countries are Malaysia, the USA, the UK,
Singapore and Saudi Arabia. Together these account for 45% of
the land under contract and 37% of all deals. Western European
investors (the top five being the UK, the Netherlands, France,
Jersey and Cyprus) are involved in 315 concluded deals, covering
nearly 7.3 million hectares, which makes this the biggest investor
region, followed by South-East Asia. Recently, the pace of
investments from the USA has slowed, while investments from
tax haven countries such as Cyprus and the British Virgin Island
have increased by comparison.
Strong regional trends
Investors from the global South show a preference for investing
in their own regions – most significantly, Malaysian investors
targeting Indonesia and Argentinian investors acquiring land
in Brazil. Similarly, investors from high-income countries tend
to target land on the same continent, such as North American
investors active in South America and East Asian investors
acquiring land in other Asian countries. European and Middle
Eastern investors are mostly active in Africa.
The private sector dominates
Private (non-listed) companies drive most of the deals: over
40% of all concluded deals, covering more than 45% of the land
under contract. This type of investor mainly targets land in Africa
and Central and South America. Stock exchange-listed firms
account for a further 30% of deals (32% of area); these deals
are concentrated more in Asia and Eastern Europe. While many
private companies are involved in a small number of deals, stock
exchange-listed companies often engage in multiple land deals
focusing on a single geographic region.
Indirect drive by investment funds and
state-owned entities
Investment funds and state-owned entities together account
for around 15% of large-scale land acquisitions and as such are
not major drivers. However, their involvement reaches further
through indirect engagement, as they are often part of highly
complex investor chains. Both investor types are shareholders in
stock exchange-listed companies, and thus provide financing to
these investors. Furthermore, government policies can stimulate
private capital to invest in foreign land acquisition.
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International Land Deals for Agriculture
Food is the main purpose, but some
investors focus on other intentions
Most investors from the top 10 investor countries are involved in
food crop production. Exceptions are the dominance of oil palm
and rubber in Asian investments and the relative dominance of
fuel crops in the case of UK and Indian investors. In particular
investment funds, and to a lesser extent state-owned entities,
appear to acquire land for food crops, according to Land Matrix
data. This underlines the drive by governments to ensure food
security for their own populations.
Most acquisitions do not include a domestic
shareholder
In 155 concluded deals, or just 15.4% of the total, equity is shared
between international and domestic investors. This indicates
that these investments have a low level of inclusion of domestic
stakeholders, limiting the impact of foreign land acquisitions
on local development. The cases with domestic shareholdings
are mostly in Africa, typically with the target government as
a joint venture partner, and the Americas. Deals involving
domestic shareholders are comparatively more focused on fuel
production.
Land acquisitions often target relatively
highly populated areas dominated by
croplands
Agricultural land deals take place in three distinct socio-ecological
contexts. On more than 50% of the area, the previous, the
previous land cover was already cropland. In areas dominated by
croplands, population densities are relatively high. This inevitably
leads to increased competition for land, and can entail an
increased incidence of conflict and loss of livelihood opportunities
for local communities. A substantial number of land acquisitions
involve forested land, which has low population densities though
land is often used by local communities. The ecological impacts
are significant, and communities are affected when forest
ecosystems are displaced by commercial plantations. A third
distinct context is moderately populated areas, often shrub- and
grasslands that are considered by outsiders to be “marginal”
areas. While many different climate zones are affected, tropical
savannah and tropical rainforest are disproportionately targeted
for land acquisition. The land targeted in Asia is mostly located
in tropical rainforests. In Central and West Africa, most deals are
concluded in tropical savannah and along major rivers outside
tropical rainforests.
Local communities are often bypassed in
negotiations
The exclusion of local communities during the negotiation phase
means that they frequently oppose foreign investors (in 60% of
the 180 deals where information is available). In about 14% of
cases, a process of free, prior and informed consent (FPIC) has
been conducted, while in 43% of cases some limited form of
consultation has taken place. It is important to note that simply
knowing that some form of consultation has taken place is not
sufficient in itself to judge the quality of the consultation process,
which can be selective and which can bypass important groups
affected by a land deal.
Limited information on displacement and
compensation
Almost half of the area targeted was formerly owned by
communities, and this is therefore likely to lead to voluntary
or forced displacements of local populations. Deals where
displacement occurs generally involve a large number of people.
Compensation is paid to people or communities who lose access
to land in one-third of cases.
Projects in operation have significant socioeconomic and ecological impacts
Typically during the start-up phase, when farms are being
established, there is high labour demand for construction work
and infrastructure development, but for a short period of time
only. However, the implications of mature operational projects
have yet to be researched in detail. Many projects have not yet
reached maturity and at this stage the Land Matrix data can
provide only limited evidence on their impacts. Many projects
promise improved social infrastructure, and Land Matrix data
suggests that education and health facilities are frequently
established. A particularly interesting aspect is the potential
creation of employment through land acquisitions. We find very
low intensities of labour, suggesting the prevalence of capitalintensive production methods and therefore limited capacity to
create rural employment. Large-scale farms are often located in
proximity to smallholder farms and hence it is likely that spillovers
to smallholder farmers will materialise. Contract farming models
are one option to include local smallholders, and Land Matrix
data shows that a substantial proportion of deals use such
models. However, these schemes are not automatically beneficial
to participants (or to non-participants), and a high degree of
involvement by investors is necessary to make contract farming
work. The environmental effects of operational farms depend
largely on the mode of production and the mitigation measures
taken. One key concern is an increase in water scarcity.
Further need for monitoring
As operational activities increase, the long-term effects on
communities will become clearer. It remains important to gain a
better understanding of the overall benefits and costs of largescale land acquisitions for local communities, rural development
and the achievement of national development goals (if any). The
trade-offs between socio-economic and environmental aims
need to be further monitored, and the impact of large-scale land
acquisitions needs to be assessed in the context of achieving the
Sustainable Development Goals (SDGs) set by the international
community.
Further need for monitoring
In the years to come the Land Matrix Initiative will continue to
collect data on land acquisitions, and will aim to forge even closer
connections with its regional partners and networks. We also plan
to develop a number of national land observatories and to work
more closely with existing multi-stakeholder platforms of various
types, helping them to further investigate the scale and impact
of land acquisitions and to contribute to policy, development,
research and advocacy activities. Eventually, we aim to use this
information to contribute to more equitable decision-making, by
supporting stakeholders with a weaker voice in negotiating and
decision-making on land acquisitions.
International Land Deals for Agriculture
» viii
1.Introduction
1.1. Background and objectives of this
report
Strong demand for land continues to be a major challenge that
highlights the interconnectedness of the global South and the
global North: investors from all over the world are acquiring
land for agriculture and resource extraction, much of it in the
global South. This phenomenon has been dubbed the “rush
for land” and has captured much attention from policy-makers,
researchers, the media and the public. A peak was reached
around 2009 during the triple crises of finance, food and fuel
(McMichael, 2012), when a series of large-scale land deals
was announced by governments and investors or reported by
researchers, non-governmental organisations (NGOs) or farming
organisations. This raised hopes for some of a faster road to rural
development, but concerns were also voiced about potential
negative effects on food security, access to land and the future
of small-scale farmers in the South by global institutions such as
the Committee on World Food Security (CFS), the UN Food and
Agriculture Organization (FAO), the United Nations Conference
on Trade and Development (UNCTAD), the World Bank, bilateral
donors and the African Union (AU).
One problem that was widely perceived by policy-makers,
researchers and the public was the scarcity of robust data. Due
to their controversial context and potential for creating conflict,
land acquisitions often take place behind closed doors. A lack
of transparency and the marginalisation of local stakeholders
weaken the bargaining position of smallholder farmers and
pastoralists, including indigenous peoples.
The Land Matrix Initiative (LMI), a partnership consisting of global
and regional partners, was established in 2009 with the aim of
addressing the lack of robust data on land acquisitions. Since
then, the Land Matrix (LM) database has recorded intended,
concluded and failed land acquisitions since the year 2000. By
providing open access to its database, the Land Matrix strives to
contribute to the overall debate by providing better information
on planned and implemented large-scale land acquisitions and
to stimulate a more transparent and inclusive debate on the
trends and impacts of such acquisitions.
The first Analytical Report (Anseeuw et al., 2012) summarised the
results of Land Matrix data collection to that date and presented
a number of important findings, based on the data available at
that time. Many of these findings have since been confirmed by
other studies.
The LMI has received much feedback and numerous
contributions over time, which have resulted in a number of
changes to the structure of the database and its data collection
methods since the first Analytical Report was published. First, the
classification system for information has been systematised, and
the classification of information as “reliable” or “not reliable” has
been dropped. The Land Matrix now provides information on
the nature of data sources and the sources themselves, allowing
users to judge the quality of information. Second, a classification
has been developed which allows the evolution of deals to
be tracked. This classification makes a distinction between
negotiation status, which captures intended, concluded and
failed deals, and implementation status, which describes activity
on the ground for deals that have been concluded. Third, the
Land Matrix has engaged regional partners and decentralised its
data collection, and has strengthened internal quality assurance.
These efforts have helped to improve both the quality and
quantity of data and are reflected in continuous updates of the
Land Matrix website. Four years after the publication of the first
Analytical Report, this second report aims to present an updated
and consolidated overview of large-scale land acquisitions,
presenting new insights based on the improved data.
Box 1: How does this report differ from the 2012 Analytical Report?
Some of the differences between the data presented in this
report and that in the first Analytical Report (Anseeuw et al.,
2012) seem quite striking at first sight. These differences can be
explained largely by four separate factors: an improvement in the
quality of data through a process of feedback and data cleaning;
changes in the methodology used to categorise data; expansion
of the LMI’s network of contributors; and finally changes in the
process of land acquisitions on the ground.
Methodological changes: We have introduced different
statuses for negotiation and now distinguish between the
intended size of a deal and the size of the contract (see also Box 3).
This has reduced the land area subject to deals considerably,
as we now only consider areas that are under contract in
our aggregate figures. We have also developed “minimum
requirements” for a deal to be shown on the public interface of
the Land Matrix. This means that many of the deals from the first
report are still held in the database but are not included in this
analysis, as we lack crucial information: for instance, we need to
know at least the country of the potential acquisition.
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International Land Deals for Agriculture
Data cleaning and feedback: The first report and the Land
Matrix website have helped to generate a large amount
of feedback. Based on this, we have corrected erroneous
information on deals and have deleted duplications (for instance,
deals with names of different investors that have proved to be
the same investment).
Expansion of the contributor network: Bringing more
regional partners on board has contributed to strengthening the
coverage of certain regions. This is particularly the case for Asia
and Latin America, which now feature more prominently in the
database than they did in 2012.
Changes in the extent of land acquisitions: A total of 276
new deals have been concluded since 2012.
These changes explain, for instance, the following differences
from the first Analytical Report.
Overall numbers: Anseeuw et al. (2012) reported 1,217
agricultural deals covering 83.2 million hectares of land, while this
report focuses on 1,004 concluded agricultural deals covering
26.7 million hectares. However, Anseeuw et al. included many
deals that did not have a contract; they only reported 403 deals
with a contract, affecting 26.2 million hectares. Their 1,217 deals
hence also included “intended” and “failed” deals, which we now
exclude for the main part of this analysis. Additionally, this total
included deals for which data was not rated “reliable”; the total
area given for deals denoted “reliable” was 32 million hectares.
Regional trends: Looking at the regional overview of target
countries (see Table 9), a regional shift can be observed: a
lower number and smaller size of deals in Asia and Africa, but
an increased number of deals in the Americas, Eastern Europe
and Oceania. In the first report, Africa accounted for 754 deals
(62% of the total) and 56.2 million hectares (67%). In the present
report, Africa accounts for 422 concluded deals (42% of all deals)
and 10 million hectares (37%) – though Africa remains the most
heavily targeted continent.
Top target countries: The top 20 target countries (Figure 11)
have also changed: some countries remain on the list (e.g. Sudan,
Mozambique, Ethiopia, Ghana), while others have dropped off
it (e.g. Tanzania, DR Congo, Senegal, Nigeria). Some, such as
Ukraine and Papua New Guinea, are new, while others have
become more important (Indonesia and Russia). Much of this
can be explained by the new focus on concluded projects and by
considering the contract size.
“The Land Matrix strives to contribute to the overall debate by providing better
information on planned and implemented large-scale land acquisitions and to
stimulate a more transparent and inclusive debate.”
Since the publication of the first Analytical Report, more research
has been conducted on land deals and more empirical results
have become available; hence both the quantity and quality of
data have increased. Together with the strengthening of the LMI
network, this has led to the addition of land deals that had not
been reported previously, and also to corrections of incomplete
or erroneous data entries.
The status of large-scale land acquisitions has continued to
develop since 2012. New deals have been signed and more
deals have begun production, while others have failed in their
implementation. In general, implementation of a substantial
proportion of deals is now starting to take place, which puts new
emphasis on the impacts of operational projects.
The present report therefore aims to fulfil two objectives: first,
to provide an updated overview and interpretation of the data
contained in the Land Matrix as of April 2016, which may serve
as a comprehensive source of this aggregated information; and
second, to capture the dynamics involved in the process of land
acquisition. We do this by providing an interpretation of the
data, illustrated by insights gathered directly from the field and
through cases studies provided by Land Matrix regional partners
and other authors linked to the LMI.
The report is structured into five main chapters. This chapter
serves as an introduction and describes the background and
objectives of the report. Chapter 2 provides an overview and
insights on regional and national trends in large-scale agricultural
land acquisitions. Chapter 3 offers an analysis of investors;
Chapter 4 looks in detail at the type of land that is targeted; and
Chapter 5 focuses on the implications of land acquisitions for
affected local communities in target countries.
1.2.The LMI: providing data and supporting
more equitable governance of land
deals
The Land Matrix Initiative is a global initiative to collect,
provide and analyse data on land acquisitions. Its goal is to
improve transparency on land deals, thereby contributing to
strengthening the positions of weaker stakeholders in the
political and administrative processes that govern access to land.
The Global Observatory of the LMI, the Land Matrix database1
(www.landmatrix.org), is an open tool for collecting and
visualising information on large-scale land acquisitions. The LMI
is coordinated by the Centre de Coopération Internationale
en Recherche Agronomique pour le Développement (CIRAD),
the Centre for Development and Environment (CDE) at the
University of Bern, the Deutsche Gesellschaft für Internationale
Zusammenarbeit (GIZ), the German Institute of Global and Area
Studies (GIGA) and the International Land Coalition (ILC). In the
context of decentralisation, four regional focal points support
the LMI with regional-level data collection, research, advocacy,
networking and communication. These focal points are the Asian
1
We use the term “Land Matrix Initiative (LMI)” whenever we refer to the partnership as an institution, while we use “Land Matrix” to refer to the data collected by
the LMI.
International Land Deals for Agriculture
» 2
Farmers’ Association for Sustainable Rural Development (AFA),
covering South-East, East, South and Central Asia; the Mongolian
NGO Jasil, covering Mongolia, Kazakhstan and Kyrgyzstan; the
Argentinian civil society organization (CSO) Fundación para el
Desarrollo en Justicia y Paz (FUNDAPAZ), covering Latin America;
and the University of Pretoria, covering Africa. The LMI is
currently funded by the German Federal Ministry for Economic
Cooperation and Development (BMZ), the European Commission
(EC),2 the Swiss Agency for Development and Cooperation (SDC)
and the French Ministry of Foreign Affairs, as well as through cofunding by the participating institutions.
The Global Observatory collects data on intended, concluded
and failed attempts to acquire land through purchase, lease or
concession for agricultural production, timber extraction, carbon
trading, industry, renewable energy production, conservation
and tourism in low- and middle-income countries. Deals must
meet the following criteria:
• Entail a transfer of rights to use, control or own land through
sale, lease or concession;
• Have been initiated since the year 2000;
• Cover an area of 200 hectares or more;
• Imply the potential conversion of land from smallholder
production, local community use or important ecosystem
service provision to commercial use.
Through the process of decentralisation and the establishment
of regional focal points, the Land Matrix is increasingly capturing
information on domestic and smaller deals. In many countries,
the distinction between purely domestic and international deals
is blurred, as ownership and control through complex structures
link national and international capital and companies in a
multi-faceted way. Although these smaller and domestic deals
have a similar impact to that of large-scale and internationally
driven projects, they fall outside the current scope of the Land
Matrix. Thus in this report we focus on deals where at least one
international investor holds equity (except where we refer to a
deal for specific reasons).
1.3.Data sources and reliability: making use
of the best available data
Data in the Land Matrix is collected from a variety of sources.
Company sources include, for example, annual reports,
corporate presentations and media releases about stock
exchange listings. Due to disclosure requirements, this latter
category is a particularly useful data source for stock exchangelisted investors. A number of governments have attempted to
increase the transparency of the large-scale land acquisitions
they are involved in and have published contracts and other
information online – for instance, Ethiopia and Liberia. In
addition, other initiatives exist that aim to promote transparency:
for example, the Land Matrix has partnered with Open Land
Contracts (http://www.openlandcontracts.org), which contains a
repository of contracts. However, while these contracts contain
detailed information, they often fail to incorporate crucial
information, such as specific locational data. Reliable and up-todate information is found in research papers and policy reports,
which are often based on on-the-ground experience. Authors
of these reports regularly provide additional information to
the Land Matrix when contacted by the regional focal points.
As such, they form part of an ever growing local network of
country informants providing updates on existing deals and new
developments. The Land Matrix also uses media publications,
which serve as a starting point to gather further information on
reported deals. Crowdsourcing is a new tool on the Land Matrix
website, but this is not yet used frequently. Figure 1 shows the
frequency of each data source as a percentage of the total.
Figure 1: All sources in the Land Matrix
29%
Media Report
24%
Company Resources
24%
Research Paper / Policy Reports
11%
Government Sources
7%
Personal Information
3%
Other
3%
Contract
Note: N (deals) = 2,155, N (sources) = 5,056. For most deals several sources are given; double-counting is included.
Source: Authors’ calculation based on Land Matrix data, April 2016.
2
The EC contribution is administered through France’s technical cooperation agency, Expertise France.
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International Land Deals for Agriculture
The quality of data has improved markedly since the 2012
report. About 29% of data sources are media reports, followed
by research papers and company sources with about 24% each.
Only 6% of all deals (127 out of 2,155) are based solely on media
reports without being backed up by any other source.
data, where using a variety of sources can significantly improve
data quality (Figure 2).
In this context, investing in decentralised data collection has
proved to be successful. The core partners and the regional
focal points have successfully established a broad network in
the different regions to obtain information and to have it crosschecked by experts, individuals working in government, the
private sector, CSOs and interested members of the public on
the ground.
The sourcing strategy can be described as “snowball sourcing”:
one source serves as a starting point for further investigation.
Thus, almost 80% of the deals reported are based on two or
more sources, and 40% have between three and seven sources.
This information increasingly allows for the “triangulation” of
Figure 2: Number of sources per deal (multiple entries)
500
400
600
5
484
57
300
700
228
Number of
sources
80
1
3
200
800
2
3
4
59
100
5
4
6
1
Source: Authors’ calculation based on Land
Matrix data, April 2016.
7
900
0
“The opaque nature of land acquisitions imposes certain limits on the datagathering process.”
Despite all efforts, however, the dataset remains incomplete.
Verification of basic data (such as deal size, location, investors
involved, terms of the lease agreement or contract) can
be challenging, with different sources providing conflicting
information. In fact, even the very existence of a deal is sometimes
difficult to prove. The opaque nature of land acquisitions imposes
certain limits on the data-gathering process. For instance, in
several countries there are no procedures for decision-making
on land deals, and negotiations and decisions do not take
place in the public realm. Furthermore, a range of government
agencies and levels of government are usually responsible for
approving land deals. Therefore even official data sources in
the same country can vary, and none may actually reflect reality
on the ground. Once a deal has been concluded, the attention
paid to it often diminishes, and so its actual development on
the ground remains uncertain to the LM team. Decisions are
often changed, and changes may or may not be communicated
publicly. Lastly, whereas intentions might be published, often
nothing is announced if these intentions are abandoned. These
limitations also introduce a number of biases to the dataset:
International Land Deals for Agriculture
» 4
•
•
Different levels of transparency regarding land acquisitions
across the world. In some countries it is easier to obtain
information than in others;
Different levels of media and research interest in certain
regions (e.g. Africa), in certain investors (e.g. emerging
investor countries) and in certain sectors (e.g. agriculture
and specifically biofuels).
The strength of the networks forged by Land Matrix partners in
different regions has an impact on the quantity and quality of
the data collected. For instance, LM partners have a stronger
network in Africa than in Central Asia.
Another challenge is the quality of sources. Data errors may arise
if the information provided by the source is inaccurate, which
can be the case for both official and unofficial sources (for an
example, see Box 2). Furthermore, information may be out of
date, as deals can change rapidly. Hence, the data presented in
this report is not to be taken as a complete representation of
reality, but rather as indicative of general trends.
Despite these limitations, the Land Matrix data represents in our
view the best available dataset on international land acquisitions.
The difficulties described above are common to any large-scale
data collection initiative. However, the sample is now sufficiently
large to reveal key patterns and trends. Given the relatively
large amount of data, and the fact that we are communicating
aggregated data, we believe that our findings are fairly robust. As
a global database, the Land Matrix data hence does a good job
in describing general trends, though it does not give detailed and
balanced insights into the processes or impacts of large-scale
land acquisitions (discussed further in Chapter 5). However, even
for the analysis of processes and implications it can serve as a
good starting point, as:
• Spatial data is (slowly) improving and allowing some land
acquisitions to be put into the local context and to be
combined with data on land use and land cover;
• There are a number of variables in the Land Matrix that
touch upon impacts, though these are often only available
for a few deals; and
• A wealth of individual cases is included in the Land Matrix,
which can be used for further investigation.
Given these challenges, we welcome further feedback that will
help us to contribute to further strengthening the Land Matrix
database.
Box 2: The pitfalls of data collection – reflections from Sierra Leone
Over the past decade, Sierra Leone has experienced an increase
in large-scale land investments, predominantly in resource
extraction and commercial agriculture. In various reports
available in the public domain, these investments are framed
either in terms of promise (as drivers of development, often in
reports produced by policy-makers) or of problems (as posing
new challenges to local communities, usually in reports produced
by NGOs). In all reports, positions appear to be straightforward
and the facts appear to speak for themselves. However, reports
on large-scale investments need to be treated carefully, as data is
collected in highly complex social fields. This case study focuses
on reports highlighting the problem perspective, as these often
enter research debates as objective sources. In addition, the Land
Matrix data draws (at least to a certain extent) on these reports
and hence often deals with conflicting and biased information.
Sierra Leone is one of the poorest countries in the world, and so
expectations of the benefits that large-scale investments might
bring are, not surprisingly, extremely high. Indeed, there is ample
evidence that many people gain from investments: this is visible,
for example, in the growth and development of towns located
near large-scale investment projects, increased job opportunities
and improved living standards, including access to material
goods. However, the effects vary across different groups of
people and, although expectations are always high, they are not
always met. This creates a fragmented social field, charged with
a desire to break with a poor past and/or frustrations over the
slow pace of development. Reports dealing with, for example,
“broken promises” by a particular investor often fail to scrutinise
this complex field of expectations. If a car was expected but
a bicycle the result, the tendency is to declare life worse than
before and promises broken, even though previously there may
have been no mode of transport at all. “What was before” is
thus very important, yet this is difficult to research. Moreover,
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International Land Deals for Agriculture
expectations are fuelled by promises made by politicians and
by companies trying to establish their projects, and by demands
imposed on companies by NGOs.
Opinions on large-scale investments thus have a particular
historical, social, economic and political context and people have
strategic interests when formulating their concerns and desires.
Furthermore, these can be framed differently according to the
interlocutor. In his work “Cultivating Development” (2005), David
Mosse shows how people carefully formulate their problems and
needs taking into account what the conversation partner is able
to deliver. This does not render these problems illegitimate, but
it does highlight that the background and perspectives of data
collectors and the framing of questions can influence results.
Moreover, the fact that in the global North funds are available to
scrutinise and make critical claims about large-scale investments
in the global South may pose further challenges in the collection
of data, as there is a pre-defined interest in a particular outcome.
As a result, findings may be skewed and the risk is that the results
will correspond with assumptions.
Short research periods for data collection contribute to these
concerns. A short period is not enough to study evolving
dynamics, let alone to contextualise statements and observations
in a longer social history. Moreover, the timing of interviews and
the people selected are key factors: discussions held during
the day might be dominated by particular groups, such as the
unemployed, for example. Using proper research methods and
careful planning is thus essential, but this is often constrained
by short time spans. It is therefore even more important to
work with researchers who have an in-depth understanding of a
particular place – which unfortunately is not always the case with
commissioned studies.
These are just a few reflections on the complexities of collecting
material in local contexts of large-scale investments, difficulties
that are frequently not acknowledged or properly understood.
They are not intended to discredit any of the work that has already
been done, but to encourage anyone to treat reports on largescale investments with caution (paying attention to the research
1.4.Scope of this report
The Land Matrix database includes deals for agricultural
production, timber extraction, carbon trading, industry,
renewable energy production, conservation and tourism in lowand middle-income countries. However, due to limited coverage
of certain sectors and in order to reduce biases in the dataset,
we have used only a sub-set of the whole database for our
global analysis, and have concentrated on those types of land
acquisition where the currently available data is most complete.
In particular, we only consider:
• Transnational deals: the Land Matrix focuses primarily on
transnational deals. Although contributions from regional
partners are leading to an increase in data on domestic
deals, this sub-set of data is not yet sufficiently rich to
provide a meaningful picture.
• Agricultural deals: The bulk of the source reports used
by the LM team focus on agricultural deals. However, in
Chapter 2 we also present a summary of forestry, tourism,
conservation and industry projects. This corresponds to
the deals currently visible on the public website of the Land
Matrix.
background and methods used and the acknowledgement/
understanding of social complexities), and not as undisputed
truths.
Source: Based on field research in Sierra Leone in 2013/2014.
Case study provided by Robert J. Pijpers, PhD fellow at the University of Oslo
and guest researcher at GIGA.
•
Concluded deals are defined as deals where we have
credible reports about an oral agreement or a signed
contract. Intended and failed deals are inherently difficult
to verify. Although they have an impact on communities, it
is extremely difficult to provide information in such cases.
Nevertheless, in certain parts of the report we refer to other
stages of the negotiation process (intended and failed deals)
and present the corresponding data.
This report is based on a snapshot of the database taken on 25
April 2016. Since the database is continuously updated, the exact
numbers in this report will differ from the information available
on the website currently.
In addition, the case studies are intended to broaden the
perspective and provide contextual information. Case studies
hence can also include deals that are excluded from the overall
analysis: for instance, we report on a mining company in Mongolia
and its impacts on local people (Box 14).
International Land Deals for Agriculture
» 6
2. Overview and Trends in Large-Scale
Agricultural Land Acquisitions
This chapter provides an overview of the data collected in the
Global Observatory of the Land Matrix. It first gives an overview
of all the data contained in the database and then focuses on
agricultural deals, where the Land Matrix has datasets that are
sufficiently solid to allow for further, more detailed analysis of
regional trends and trends in implementation.
Figure 3: Data overview
1 549
36
2.1. Overview of all deals
34
97
2.1.1. Database contains 1 549 deals in total
One important feature of the Land Matrix is the methodology it
uses to differentiate key stages in the negotiation process of land
deals. As land acquisitions are dynamic processes, it is important
to report on the evolution of deals, from their announcement to
the conclusion of a contract and the project’s implementation, or
even its failure. Sometimes cases also evolve further over time,
e.g. a deal can be cancelled but is later renegotiated by other
investors. The Land Matrix tracks deals that have a concluded
contract but also deals that are not yet concluded (intended
deals) and deals that have failed.3
As shown in Figure 3, the Land Matrix currently has details of
1,549 land acquisitions in which at least one foreign investor
is involved, across all the different negotiation statuses. Table
1 provides an overview of these deals, also showing their size
(differentiating between the intended size and the contract size;
for more on this, see Box 3).
in the database
63
155
212
57
Concluded
1 204
1 132
Intended
Failed
72
Oral agreement
Contract signed
Expression of interest
Under negotiation
Negotiations failed
Contract cancelled
No Information
Source: Authors’ calculation based on Land Matrix data, April 2016.
Table 1: All international land acquisitions recorded in the Land Matrix database
NEGOTIATION STATUS
NUMBER OF DEALS
SIZE INTENDED
(MILLION HECTARES)
CONTRACT SIZE
(MILLION HECTARES)
Oral agreement
72
4.6
2.2
Contract signed
1 132
52.6
40.3
Concluded deals
1 204
57.2
42.4
Expression of interest
57
8.3
n/a
Under negotiation
155
12.0
n/a
Intended deals
212
20.2
n/a
Negotiations failed
63
6.0
n/a
Contract cancelled
34
1.2
0.9
Failed deals
97
7.2
0.9
No information
Total number of deals in the Land Matrix
36
0.9
0.2
1 549
85.5
43.6
Note: “n/a” stands for “not applicable”.
Source: Authors’ calculation based on Land Matrix data, April 2016.
3
For a more detailed explanation of the methodoly, please refer to http://landmatrix.org/en/about/.
7 »
International Land Deals for Agriculture
Intended deals can be considered an indication of future interest
in land. Table 1 takes stock of 212 intended deals, targeting a
total of 20.2 million hectares; hence we assume that interest in
land remains high. However, looking more closely at sources,
out of 169 deals for which we have this information, 125 (74%)
have sources dating from before 2012. For these cases, it seems
that implementation is uncertain or even unlikely; however, it is
important to note that such deals can still have an impact on
the target regions even though they are not operational – for
instance, they could become a barrier to other development
activities or investments by current land users.
Box 3: Size variables and conflicting information on the size of deals
The size of a deal is an important aspect that has caused some
confusion amongst Land Matrix users in the past. The LM
records three different size variables to give an accurate and
realistic picture. The first time a deal is mentioned, for instance
in a media report, we often find out only the intended size.
This is frequently the size mentioned during the negotiation
phase. Typically, this size exceeds the contract size (see Table 1)
when the deal is formally agreed. The size that is actually under
production (production size) is the most difficult to ascertain, as
it keeps changing during the implementation stage when the
farm expands its agricultural area. In cases where the production
size is known but not the contract size, we use the production
size as a proxy for the contract size.
The 97 failed deals show that not every expression of interest
in land leads to a contract (negotiations fail), and also that some
deals fail even after agreement is reached, resulting in the
cancellation of a concluded contract. However, even though a
contract might be cancelled, the initial acquisition may continue
to have impacts on the target region as the land is often not
returned to the original owners.
agricultural area and are equivalent to more than the total area
of Germany (35.7 million hectares).
Looking at the 1,204 deals that have been concluded (oral
agreement and contract signed), it can further be seen that
the size of land that has come under contract is well below
the size that was initially intended (see below). Still, to put this
into perspective, the 42.4 million hectares of land that have
come under contract represent about 0.8% of the world’s total
In general terms, a broad range of figures quantifying the
extent of land acquisitions can be found in online sources.
Often, however, these figures differ significantly, for a number
of reasons: for instance, the definition of the term “large-scale
land acquisition”, the timeframe and the size and logic used for
aggregation.
2.1.2.
Size of deals
Looking at the intended size of deals in terms of the different
negotiation statuses (see Table 2), Land Matrix data shows
that deals that have been concluded are considerably smaller
in size than deals that have failed and those that are intended.
This indicates that projects of an exceptionally large scale might
face a number of issues that can only be dealt with on a smaller
scale. For example, managerial and technical difficulties may
arise during the implementation phase, especially in challenging
ecological, political and socio-economic environments.
Table 2: Intended size of deals according to different negotiation statuses
NEGOTIATION
STATUS
MINIMUM
(HECTARES)
MAXIMUM
(HECTARES)
MEDIAN
(HECTARES)4
MEAN
(HECTARES)
NUMBER OF
DEALS
TOTAL SIZE
INTENDED
(MILLION
HECTARES)
Failed
200
1 000 000
20 000
74 406
97
7.2
Intended
400
1 500 000
19 000
95 511
212
20.3
Concluded
221
619 759
10 000
47 484
1 204
57.2
Source: Authors’ calculation based on Land Matrix data, April 2016.
“Deals that have been concluded are considerably smaller in size than deals that
have failed and those that are intended.”
4
The median is the “middle value”: half of the data sample is below and half of the data sample is above this value. Compared with the mean, the median shows if
data is skewed by very high or very low values. Here, the median is much lower than the mean, indicating that some very high values are skewing the mean.
International Land Deals for Agriculture
» 8
State-owned companies and governments are particularly
noticeable for the large average size of their deals in the intended
phase but a smaller than average deal size when a contract is
concluded. It should be noted that state-owned entities also have
the lowest rate of concluded deals as a percentage of all deals
(63.9% for government-related investors compared with 78%
for all investor types – “other” and “no information” categories
excluded) and have the highest percentage of failed deals (15%
versus 7% overall).
Investigating the size of land under contract for the 1,204
concluded deals (57.2 million hectares), we see from a mean of
35,756 hectares and a median of 8,650 hectares that some very
large deals are driving these results. Table 3 shows the number
of deals according to different size classes, which confirms that
almost three-quarter of deals are for less than 20,000 hectares,
while only 13% of deals are for more than 50,000 hectares.
Table 3: Number of concluded deals according to contract size
Size under contract (hectares)
Number of deals
%
200 to 2 000
233
19%
2 001 to 5 000
185
15%
5 001 to 10 000
280
23%
10 001 to 20 000
161
13%
20 000 to 50 000
165
14%
50 000 to 200 000
112
9%
More than 200 000
45
4%
No information
23
2%
Source: Authors’ calculation based on Land Matrix data, April 2016.
2.1.3.
Choice of contracts shows a clear
regional pattern
Table 4 shows the different types of contract recorded in the
Land Matrix according to target continent. It can be seen that
deals in Africa, Asia and Oceania almost exclusively use leases
or concessions, while deals in the Americas focus on outright
purchases. For deals in Eastern Europe, both options seem to
be used frequently. Note that a concession implies user rights
(and not a transfer of property rights); this type of contractual
agreement is commonly used for forestry and mining projects.
Table 4: Nature of deals, by continent
TARGET CONTINENT
LEASE/CONCESSION
(NUMBER OF DEALS/%)
OUTRIGHT PURCHASE
(NUMBER OF DEALS/%)
TOTAL (NUMBER OF
DEALS)
Africa
376
94%
22
6%
398
Americas
20
10%
176
90%
196
Asia
207
96%
8
4%
215
Eastern Europe
38
72%
15
28%
53
Oceania
40
98%
1
2%
41
Total
681
75%
222
25%
903
Source: Authors’ calculation based on Land Matrix data, April 2016
These clear regional patterns can be explained by national laws:
many countries, particularly in Africa, Asia and Oceania, do not
allow the outright purchase of land, and in these cases land is
often transacted between the government and an investor.
Other countries, such as Brazil, allow land ownership by foreign
companies and persons but impose limitations. In Latin America,
land is often transacted between private entities. Lease contracts
typically have a long duration. For 327 deals with lease contracts
9 »
International Land Deals for Agriculture
for which information is available, the duration of the lease
ranges from three years to 99 years, and 94% of these leases
run for at least 20 years. Again, the data shows that national
legislation plays a major role in lease contracts: for example, 56
Cambodian deals have a duration of 70 years, 31 deals in Papua
New Guinea last for 99 years and Zambia only allows leases of 99
years. Investors might also be averse to investing directly in land
ownership and may prefer lease constructions.
2.2.Investment intention: focus on
agriculture
Table 5 reports the investment intention of all concluded deals in
the database, as given in the sources.5 For the majority of deals –
both in terms of the number of times an intention is mentioned
(many deals report more than one intention) and the respective
size – agriculture is the predominant intention.
Table 5: Intention of land acquisitions
INTENTION
NUMBER OF TIMES INTENTION IS
MENTIONED
TOTAL CONTRACT SIZE
(MILLION HECTARES)
1 403
24.1
– Agrofuels
221
5.1
– Food crops
553
9.2
– Livestock
130
2.0
– Non-food agricultural commodities
236
2.3
– Agriculture (unspecified)
263
5.6
Forestry
187
12.0
Tourism
25
1.7
Industry
33
0.4
Conservation
20
1.4
Renewable energy
57
0.9
Other intention
28
1.0
No information
30
1.0
Agriculture
Total
1 783
Note: Individual deals can have up to five different intentions listed. The Land Matrix does not provide information on the share of area for each intention; hence for
this report we have divided the area under contract and attributed equal shares to each intention. We count the number of times an intention is mentioned and for
N (deals) = 1,204, we report N (intentions) = 1,783.
Source: Authors’ calculation based on Land Matrix data, April 2016.
Figure 4 shows the agricultural intentions of concluded deals, as
recorded in the sources. Food crops continue to play the major
role, both in terms of numbers of deals and total area, followed
by agrofuels. The large proportion of deals (23% by area) that do
not specify the intention of agriculture any further can largely be
attributed to flex crops6 for which the end use is not known. Oil
palm is the largest of these crops, with multiple usages including
food, fuel and cosmetics.
Looking solely at recent deals concluded since 2012, the category
“agriculture unspecified” is even larger, accounting for 32% of the
area, while agrofuels (18%) and food crops (36%) have a slightly
smaller share.
Figure 4: Agricultural intentions of land acquisition (% of area)
21%
Agrofuels
38%
Food Crops
9%
Livestock
9%
Non-food Agricultural Commodities
23%
Agriculture (unspecified)
Note: Individual deals can have up to five different intentions listed. The Land Matrix does not provide information on the share of area for each intention;
hence for this report we have divided the area under contract and attributed equal shares to each intention.
Source: Authors’ calculation based on Land Matrix data, April 2016.
5
6
The variable “intention” in the database records what the sources state on the intention of the investment and is not automatically derived from the crops involved.
Flex crops have multiple end uses, for example as food, animal feed, fuels or industrial materials.
International Land Deals for Agriculture
» 10
As illustrated in Table 6, there are some quite noticeable regional
differences in agricultural intentions: for instance, agrofuels
are the largest intended crops in Africa and on the American
continent and are also significant in Asia and Oceania, but are
negligible in Europe. Food crops are important everywhere but
are particularly significant in Europe and the Americas, where
they occupy almost half of the acquired area. Livestock deals
play hardly any role in Africa or Asia, but are quite important in
Europe and the Americas.
Table 6: Agricultural intentions across regions (% of area)
AFRICA
EUROPE
AMERICAS
ASIA
OCEANIA
GLOBAL
Agrofuels
32%
1%
29%
16%
16%
21%
Food crops
39%
45%
50%
21%
30%
38%
Livestock
3%
17%
16%
1%
11%
8%
Non-food
agricultural
commodities
9%
1%
1%
29%
3%
9%
Agriculture
(unspecified)
17%
37%
4%
33%
40%
23%
Note: Individual deals can have up to five different intentions listed. The Land Matrix does not provide information on the share of area for each intention; hence for
this report we have divided the area under contract and attributed equal shares to each intention.
Source: Authors’ calculation based on Land Matrix data, April 2016.
Land Matrix data also allows investigation of the crops that
investors grow: we have information on individual crops for a subset of 930 concluded deals. Figure 5 shows different categories
of crop according to FAO’s Indicative Crop Classification (ICC).
The majority fall into the categories of oilseed crops, including
oil palm and jatropha (44%), and cereals (20%), followed by sugar
crops (10%).
Figure 5: Crops cultivated (% of area)
44%
Oilseed Crops
20%
Cereals
10%
Sugar Crops
3%
Trees
3%
Beverage and Spice Crops
3%
Root/tuber Crops with High Starch or Insulin Content
17%
Other Crops
Note: Based on FAO’s ICC classification, in percentage of area under contract. Individual deals list up to seven different crops. The Land Matrix does not provide
information on the share of area for each crop; hence for this report we have divided the area under contract and attributed equal shares to each crop. We
have counted the number of times a crop is mentioned and for N (deals) = 930, we report N (crops) = 2,007.
Source: Authors’ calculation based on Land Matrix data, April 2016.
“Most significant are projects for oil palm cultivation, followed by jatropha and
sugar cane.”
11 »
International Land Deals for Agriculture
“Looking at the most significant crops in more recent deals (since 2012), jatropha
loses importance.”
Figure 6 looks further into individual crops and shows the most
important ones according to the size of land under contract.
Most significant, with almost 6 million hectares (220 deals), are
projects for oil palm cultivation, followed by jatropha (2.4 million
hectares, 92 deals7) and sugar cane (1.9 million hectares, 92
deals). The average size of deal varies considerably, as can be
seen from the number of times a crop is mentioned and the
size of area for each crop. Looking at the most significant crops
in more recent deals (since 2012), jatropha – which is most
commonly cultivated as a biofuel – loses importance, with only
four new deals in the last four years. Also, many jatropha deals
are being abandoned: of 97 failed deals, 20 involve jatropha.
250
Area (in hectares)
7 000 000
6 000 000
200
5 000 000
150
4 000 000
3 000 000
100
2 000 000
50
1 000 000
Number of times a crop is
mentioned
Figure 6: Leading crops according to area under contract
0
Area used for crop (in ha)
Barley
Sun Flower
Rice
Soya Beans
Wheat
Corn
(Maize)
Rubber
Sugar Cane
Jatropha
Oil Palm
0
Number of Deals per crop
Note: Individual deals list up to seven different crops. The Land Matrix does not provide information on the share of area for each crop; hence for this report
we have divided the area under contract and attributed equal shares to each crop.
Source: Authors’ calculation based on Land Matrix data, April 2016.
2.3.The “rush for land” is moving towards
the implementation phase
Figure 7 shows the trend in reports of concluded agricultural
deals contained in the Land Matrix from 2000 to 2016. There was
a steep increase in deals around 2005, and a levelling out around
2012. The slower growth in recent years does not necessarily
mean that fewer deals are being concluded: it might also be
caused by a time lag in the availability of information, since it
often takes some years before a land acquisition becomes
known publicly. Reasons that would explain a real slowdown –
meaning a decrease in the rate of land acquisitions – could
include the financial crisis, a decrease in commodity prices or
social unrest. At present we are not able to distinguish whether
the levelling out is due to a reporting bias or to a real decrease
in land acquisitions. However, it is worth noting that the same
trend of levelling off was seen for 2010 in the previous Analytical
Report and that this has now disappeared – an indication that
reporting bias plays an important role.
7
Although many jatropha deals have failed, the Land Matrix still contains details of 92 jatropha deals with a concluded contract. Of those, 17 are in the start-up phase
and 33 are in operation. Of the remainder, five have not started, 22 have been abandoned and for 15 the implementation status is unknown.
International Land Deals for Agriculture
» 12
Figure 7: Transnational agricultural deals with a concluded contract, 2000–2016
900
25 000 000
700
600
15 000 000
500
400
10 000 000
300
200
5 000 000
Number of deals
Area (in hectares)
800
20 000 000
100
0
Area size under contract (N=833 deals, 23.8 million ha in 2016)
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
0
Number of Deals under contract
Note: Figures for size and number of deals are cumulative. For 171 concluded deals, the year in which the deal was concluded is unknown.
Source: Authors’ calculation based on Land Matrix data, April 2016.
Once a contract is concluded, we can see whether deals are
implemented or not. There can be many reasons for a failure
to develop the land, including financial constraints, management
problems or land price speculation (see Box 4).
Box 4: Large-scale projects forced to scale down by target governments
In 2009 Herakles Capital, a US venture capital firm, signed
a 99-year memorandum of understanding (MoU) with the
Government of Cameroon for 73,086 hectares of land (Case
#1159 in the Land Matrix).8 The lease was signed in 2013;
however, the government allocated the company only 19,843
hectares for oil palm production. The lease was for three years,
with an option to extend to 99 years depending on the initial
investment. However, operations were suspended in 2013 after
fierce criticism and protests from the local population and civil
society. By 2015 the company was in a dire financial situation
and, in order to address this, began exporting timber to China.
Evidence came to light of a range of breaches of regulations in
the plantation’s licensing and operation; however, it came under
new leadership late in 2015 and land clearing has continued –
indeed, its pace has accelerated. The company appears to have
focused its efforts on salvaging land for oil palm production near
the town of Nguti, while forsaking its other sites near the towns
of Mundemba and Toko.
In Ethiopia an Indian investor, Karuturi Global Limited, obtained
an MoU for 300,000 hectares in 2008 for a period of 99 years
(Case #1205). In 2010 the federal government reduced the size
of the agreement to 100,000 hectares for 50 years, as 300,000
hectares was deemed excessive and beyond the company’s
capacity for development. The full 100,000 hectares was meant
to be cultivated within two years from the date the contract
was signed, and the government gave the company two written
warnings that the land would be taken away unless it was brought
into full production. Subsequently, the land under contract was
further reduced from 100,000 hectares to 1,200 hectares in
2015. Karuturi is challenging the government over this; it has
obtained a court order protecting the lease and is prepared to
seek international arbitration.
Meanwhile in Zambia, Wuhan Kaidi, a Chinese company, wanted
to acquire 300,000 hectares of land for biofuel production and
signed an MoU for 80,700 hectares (Case #3739). However,
when it signed the lease agreement in 2011 the size was reduced
to 4,000 hectares. This followed a change of government; the
new President said that only 4,000 hectares would be granted,
with an increase if the company performed well. The investor
abandoned the project, stating that the land offered was
inadequate to justify the $450 million project.
Source: Land Matrix, 2016.
Case study provided by Angela Harding, University of Pretoria, Regional Focal
Point Africa.
8
You will note that some of the boxes mention specific deals that have ID numbers. These ID numbers correspond to the Land Matrix ID so that you can look them
up on the Land Matrix homepage (www.landmatrix.org).
13 »
International Land Deals for Agriculture
In order to account for the dynamics of implementation, the Land
Matrix not only distinguishes between the different negotiation
statuses with different size variables (as discussed above) but
also defines four different stages of implementation applicable
only to concluded deals. These implementation statuses are:
• Project not started: no activity is taking place on the land.
• Start-up phase: there is activity on the ground but no
production is yet taking place. For example, the ground
has been cleared or a nursery for tree crops has been
established.
• In operation: projects are actually producing.
• Abandoned: projects have come to a halt after a contract has
been concluded. These projects may stop only temporarily
due to financial constraints or other problems, but move to
the “failed” category when there is no chance that they will
restart operations. It is important to note that for abandoned
projects the land still belongs to the investor, whereas in
failed deals the investor has relinquished ownership of the
land (lease or purchase).
Table 7 compares recent figures on implementation status
with figures published in the Land Matrix Newsletter in June
2013.9 From this comparison, two major trends emerge. First,
our database is growing: we can see that all of the different
implementation statuses have more cases today compared with
June 2013. Second, the data quality is improving, as indicated
by fewer deals in the “no information” category. Third and most
interestingly, deals are now actually being implemented. The
biggest increases in numbers of deals are in the categories
of “start-up phase” (+54%) and “in operation” (+87%): we now
have 710 deals that have at least started implementation, on
a contracted land size of 18.5 million hectares (about half the
size of Germany). It remains difficult to track the area under
production, though currently the Land Matrix records 6.4 million
hectares that are reported to be under production, almost
quadruple the area in June 2013. The data on implementation
status strongly suggests that the rush for land has now entered
its implementation phase, though we are yet to see the full
impacts of these deals.
Information on the implementation of deals is particularly difficult
to obtain, as this information can change rapidly and might not
be reported as prominently as the acquisition itself.
“Slower growth in recent years does not necessarily mean that fewer deals are being
concluded: it might also be caused by a time lag in the availability of information.”
Table 7: Implementation status of agricultural deals
IMPLEMENTATION
STATUS
NUMBER OF CONCLUDED
DEALS
CONTRACT SIZE (MILLION
HECTARES)
SIZE IN PRODUCTION
(MILLION HECTARES)
April 2016
June 2013
April 2016
June 2013
April 2016
June 2013
Project not started
63
49
2.8
3.4
n/a
n/a
Start-up phase (no
production)
106
69
2.0
2.4
n/a
n/a
In operation (production)
604
323
16.5
12.0
6.4
1.7
Project abandoned
37
35
1.1
2.1
n/a
n/a
194
279
4.3
12.4
n/a
n/a
1 004
755
26.7
32.3
6.4
1.7
No information
Total
Note: “n/a” stands for “not applicable”.
Source: Authors’ calculation based on Land Matrix data, April 2016.
However, it is unclear whether the figures presented in Table 7
show the dynamics on the ground or rather the dynamics of the
LM database. For a small sub-set of deals, the Land Matrix data
has more detailed information; below we present three such data
9
sub-sets that allow us to understand the underlying dynamics
of implementation. In these cases, Land Matrix data reflects the
development of deals over time and not the development of our
data collection efforts.
The newsletter can be accessed here: http://landmatrix.org/media/filer_public/2013/06/10/lm_newsletter_june_2013.pdf
International Land Deals for Agriculture
» 14
First, Figure 8 shows the sub-set of deals for which we know
the size under production (N = 330). We compare how the area
under contract and the area under production have developed
between 2000 and 2016. As in Figure 7, we see a steep rise
in the area under contract between 2005 and 2014. The area
under production has developed only very slowly alongside land
acquisitions, but has been on a steep growth curve since 2010.
Today, 55% of the area under contract has been brought into
production for this sub-set of deals. This clearly shows that for
those deals that are being implemented, investors are bringing
land under production at a growing rate.
Figure 8: Development of land size under contract and size under operation
60
50
3 000 000
40
30
6 000 000
20
3 000 000
% Area Size
Area (in hectares)
12 000 000
10
0
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
0
Year
% of area under production
Area size under contract
Area size under production
Source: Authors’ calculation based on Land Matrix data, April 2016.
Table 8 gives only the most recent status but contains information
on intermediate statuses in the footnotes.
Table 8 shows a sub-set of deals for which we know more than
one implementation status (N = 117)10 and hence can follow the
implementation of an individual deal. We see that the majority of
these deals have changed from “start-up phase” to “in operation”
(82), while 20 deals have been abandoned.
Table 8: Transition from first reported implementation status to current implementation status
Current implementation status
First reported
implementation status
PROJECT NOT
STARTED
START-UP
PHASE (NO
PRODUCTION)
Project not started
Start-up phase (no production)
IN OPERATION
(PRODUCTION)
1
4
82
Project abandoned
1
1
13
5
91
TOTAL
8
8
11
In operation (production)
Total
PROJECT
ABANDONED
12
98
8
9
1
2
20
117
12
Note: “n/a” stands for “not applicable”.
Source: Authors’ calculation based on Land Matrix data, April 2016.
Most of these deals have information on two implementation statuses; four deals have three different statuses.
This is Case #1872, where the investor established a nursery in 2008. In 2012 activities were halted due to financial problems, but in 2014 the company began
production – so this deal is now under production.
12
Four of these deals have three different implementation statuses: they have moved from “start-up phase” to “in operation,” and are marked as “project abandoned”
in the most recent stage.
13
Abandoned projects may be abandoned only temporarily, as shown by one deal that has moved from the “abandoned” to the “start-up phase” category. This is Case
#1498, the Markala sugar project in Mali: the project faced political and financial challenges, but the stakeholders have been able to partly revive it.
10
11
15 »
International Land Deals for Agriculture
Figure 9 shows the time that deals need to transit from either
the implementation status “project not started” (N = 8, displayed
in green) or “start-up phase” (N = 86, displayed in orange) to an
implementation status of “in operation.” Most deals enter the
production phase in less than three years and more than half in
less than two years.
Figure 9: Years needed for projects to move to production phase
Number of Deals
30
3
25
20
1
15
5
25
2
10
17
16
11
2
0
0
1
2
5
4
3
4
6
5
2
6
Information
Missing
Years needed to move towards production
Start up Phase
Project not Started
Note: N = 94 projects transiting from “project not started” and “start-up phase” to production.
Source: Authors’ calculation based on Land Matrix data, April 2016.
2.4. Regional trends and top target
countries
2.4.1. Africa remains the most targeted continent
Africa remains by far the most targeted continent, with 422
concluded agricultural deals involving a total area of almost 10
million hectares (Table 9), according to Land Matrix data. Asia has
the second largest number of deals, with 305 deals involving 4.9
million hectares. Eastern Europe has only 96 deals but in terms
of total size accounts for more than 5 million hectares, while Latin
America is represented with 146 deals and 4.5 million hectares.
Oceania, which in the context of the Land Matrix includes only
Papua New Guinea and the Pacific islands, is the least targeted
region, with 35 deals on 2.2 million hectares; however, overall,
the average deal size is largest in this region.
Table 9: Continental breakdown of target regions for agricultural deals
REGION
NUMBER OF CONCLUDED DEALS
TOTAL SIZE OF CONCLUDED DEALS
(MILLION HECTARES)
422
10.0
Africa
Eastern Europe
96
5.1
Asia
305
4.9
Latin America
146
4.5
Oceania
Total
35
2.2
1 004
26.7
Source: Authors’ calculation based on Land Matrix data, April 2016.
International Land Deals for Agriculture
» 16
Figure 10 depicts the 943 geo-referenced agricultural
deals contained in the Land Matrix in a heat map, with the
concentrations of land deals highlighted in intensity from yellow
to orange.
Figure 10: Global heat map of land deals contained in the Land Matrix
Note: In this heat map, high
densities of 943 concluded
agricultural deals at different
levels of geospatial accuracy are
shown in orange, transitioning
into yellow for lower densities.
The map was created using the
Kernel Density tool in ArcGIS
10.3 mapping software, with
a search radius of 5 decimal
degrees.
Source: Land Matrix, 2016.
Looking at Africa, the map shows a concentration of land
acquisitions in West Africa and in Eastern Africa, stretching
from Sudan to Mozambique. It not only shows which countries
have been targeted, but more importantly it highlights the
patterns of concentration of land deals within the target regions
and countries. This gives an indication of the factors that may
influence the choice of location for a land deal. For example, the
area along the River Nile is visible, indicating that in a dry area
agricultural land deals are concentrated where water is available.
This effect can also be observed in northern Senegal, where a
large number of land deals have been completed along the
Senegal River, and in Mali along the Niger.
Within large countries, some areas of higher concentration are
clearly highlighted – for instance, in the southwestern corner of
Russia. In Eastern Europe, Bulgaria and Romania also have many
reported deals.
Land Matrix records on deals in Asia originate mainly from a few
countries in South-East Asia, including Cambodia, Laos, Indonesia
and the Philippines. An example of where data is missing in this
region is Myanmar, a country that is not well represented in the
database, despite reports of a high incidence of land acquisitions
in that country (Global Witness, 2015).
17 »
International Land Deals for Agriculture
2.4.2.
Top target countries
Beyond this global overview, a more detailed analysis of the Land
Matrix data reveals a considerable concentration of deals in a
small number of countries. Figure 11 shows the top 20 target
countries, with concluded deals according to the size under
contract. Together they account for 21.9 million hectares for
675 concluded deals (82% of the total size of all concluded
agricultural deals and 67% of the total number).
The top five target countries alone, where the international
acquisition of agricultural land is most concentrated, account for
46% of the total size of all concluded agricultural deals (25% of the
total number). These countries are Indonesia, Ukraine, Russia,
Papua New Guinea and Brazil. With the exception of Papua New
Guinea, these countries are also characterised by large areas of
acquired land that are already in operation (9.4 million hectares
out of 12.2 million hectares in these five countries).
The percentage of land that is already under operation, however,
varies greatly between countries. The different colours in Figure
11 show the different implementation statuses of deals. In some
countries, large areas have been taken under contract but large
parts of these areas are not yet in production, e.g. in Papua New
Guinea, Argentina and South Sudan. In other countries, large
areas are in the start-up phase and so further development
can be expected in the years to come, e.g. in Ethiopia,
Cambodia and Zambia. Some countries are very far advanced
with implementation. For instance, all deals in Paraguay are
in operation, as are the majority of deals in Russia, Indonesia,
Ukraine and Brazil. In other countries abandoned projects
account for quite large areas, for instance Madagascar. In some
countries, we do not have any information on implementation
status, for instance Morocco, Indonesia and Cambodia. These
figures can be significantly affected by one large deal or by a
bigger number of small deals.
The dots represent the number of deals in these top target
countries. Some countries have only a very few deals but they
are large (e.g. Ukraine, Morocco or the Republic of Congo), while
others have many deals but a relatively small total area (e.g.
Cambodia and Mozambique). The top target country, Indonesia,
has the most deals in terms of both size and numbers. If the
list of top target countries were determined by the number
of concluded deals, we would lose countries with only a few
deals (South Sudan, Morocco, Congo, Liberia, Madagascar and
Paraguay), and instead have Romania (44 deals), Uruguay (32),
Tanzania (31), Nigeria (20), Senegal (14), the Philippines and
Uganda (14 each) in the top 20.
Figure 11: Top 20 target countries according to size of concluded deals (showing different implementation statuses)
140
3 500 000
123
2 500 000
100
95
80
2 000 000
61
1 500 000
60
60
49
45
Startup Phase
26
10
Abandoned (size in ha)
Laos
Mozambique
Paraguay
0
Sudan
Republic of Congo
7
9
Madagascar
Morocco
Under Operation (size in ha)
20
18
Liberia
5
Sierra Leone
4
Cambodia
3
South Sudan
20
Ethiopia
Argentina
Russia
Ukraine
Indonesia
0
Not Started (size in ha)
26
25
Brazil
23
500 000
40
32
Zambia
34
Ghana
1 000 000
Number of Deals
120
Papau New Guinea
Area (in hectares)
3 000 000
No Information
Note: dots indicate the number of deals (right y-axis), bars indicate the size of land (left y-axis).
Source: Authors’ calculation based on Land Matrix data, April 2016.
2.4.3. Many deals take place in a context of poverty
and food insecurity
To understand the environment in which large-scale land
acquisitions take place and hence the potential impact on the
target country, and also to understand the context that is likely
to attract investors, this section provides a perspective on the
socio-economic indicators of the most targeted countries.
International Land Deals for Agriculture
» 18
Figure 12: Typology of land acquisitions according to the Global Hunger Index 2015 and agricultural GDP
16.6
10
5
50
SLE
Agriculture as % of GDP
ETH
40
Land Acquired
as percentage
of agricultural area
KHM
TZA
30
LAO
PRY
20
GHA
GIN
MAR
10
UKR
0
0
MDG
NGA
IDN
ZMB
URY
ARG
ROU
MOZ
COG
BRA
5
RUS
10
15
20
25
30
35
40
45
Hunger Index
The size of the bubble represents the area of acquired land relative to the available agricultural area in any given country
Note: This figure shows 21 of the 25 top target countries with the largest areas of reported land acquisitions; due to a lack of data, Papua New Guinea, Sudan,
South Sudan and Liberia have been omitted. In comparison with the top 20 target countries presented above in Figure 11, this figure adds the next five most
targeted, namely Uruguay (URY), Romania (ROU), Guinea (GIN), Tanzania (TZA) and Nigeria (NGA). Due to a lack of data, the figure for Zambia on agriculture’s
percentage of GDP is not from 2014 but from 2013. Country abbreviations are based on the ISO 3166-1 alpha-3 standard: UKR (Ukraine); ARG (Argentina);
RUS (Russia); BRA (Brazil); MAR (Morocco); PRY (Paraguay); GHA (Ghana); IDN (Indonesia); COG (Congo, Republic of); ZMB (Zimbabwe); KHM (Cambodia); LAO
(Laos); MOZ (Mozambique); MDG (Madagascar); ETH (Ethiopia); SLE (Sierra Leone). The x-axis indicates the Global Hunger Index (GHI): the higher the number
the more severe is hunger, as measured by a multi-dimensional index (http://www.ifpri.org/topic/global-hunger-index). The y-axis gives the percentage of
agricultural GDP of the total GDP. The size of the bubbles indicates the percentage of the contracted area related to the agricultural area. The dotted lines
show the corresponding mean value for the countries depicted.
Data: Land Matrix 2016, World Bank 2014, FAO 2016, IFPRI 2015.
Figure 12 depicts the top target countries in a matrix representing
them in terms of the incidence of hunger and the contribution
of agriculture to their gross domestic product (GDP). In order
to put the area of acquired land into perspective, the figure
represents the share of land acquired as a percentage of the
total agricultural land in a given country.14 This representation
shows that there are two main target groups of countries. The
first group consists of countries with a high GHI and a high
dependence on their agricultural sectors. These countries can
be seen in the upper right corner of the graphic, and include
Laos, Cambodia and Sierra Leone. On the one hand, this result is
in line with economic arguments that support land acquisitions
as a means of attracting investments in agriculture, with the aim
of producing more food and creating jobs. If these investments
create substantial numbers of jobs and produce food for domestic
markets, then they might contribute to eradicating hunger and
poverty in those countries, according to this line of reasoning.
On the other hand, these potential benefits need to be weighed
against the potential loss of land to small-scale producers and
indigenous peoples, who are often highly dependent on land
for their own food security and have few alternatives for income
generation. If the land acquired is used for the production of
biofuels or food destined for export markets, then such benefits
are even less obvious, although the potential contribution to
rural development still needs to be factored in.
Countries such as Russia, Ukraine, Brazil and Uruguay represent
the second group, clustered in the lower left corner. Countries in
this group have a much lower GHI and agriculture is proportionally
less important to their national economies. In this group, the
context and hence the process is very different from those in the
first group. For instance, in Eastern Europe land acquisitions take
place in the context of a transition from centrally planned state
economies to more capitalist and free market economies, which
has involved unique challenges (see Box 5). In South America,
unlike other continents, land acquisitions mostly involve the
purchase of land in transactions between private land-owners,
without the involvement of the state as an intermediary (see
Chapter 3).
14
When interpreting these results, it must be taken into account that the comparison is made with agricultural areas as defined by FAO, i.e. they include arable land,
permanent crops and grazing land, and that some of the land acquired is land that was previously used as pastures or forests, and not only arable land.
19 »
International Land Deals for Agriculture
Box 5: Eastern Europe – a special history in the development of land ownership
The post-socialist countries in Eastern Europe have distinctive
conditions that highlight the influence of local economic
and political circumstances and of policy frameworks on the
specificities of large-scale land investments. Belarus, Ukraine,
Romania, Russia and Bulgaria (the countries in this region
featured in the Land Matrix) have all experienced a similar course
of development of land ownership and use, which ultimately
has seen collective farms replaced by large-scale agricultural
enterprises.
large-scale investors, both international and local; some of these
investors started life as newly created non-state businesses in
the immediate post-socialist period. Such investments, which
often involve collaboration between local companies and foreign
investors, have seen deals involving areas of up to 654,000
hectares, as in the case of UkrLandFarming’s operations in
Ukraine. Usually, the land used by these companies is acquired
through leaseholds, joint ventures or the merger and acquisition
of smaller players (as is often the case in Ukraine, for instance).
After the collapse of the USSR, these countries reorganised land
ownership by distributing land plots amongst the population, to
be used for their own production. The assets of collective farms
were fragmented and small parcels of land (of about 0.4 hectares)
were granted to citizens – either to “those who work it”, as in
Ukraine (OSW, 2014) or to the “original” owners, as in Bulgaria
(TNI, 2013) – and to newly created non-state businesses. In most
cases the new land-owners were not issued with title deeds. As a
result, large areas of agricultural land in Eastern European remain
(nominally at least) in the hands of a vast number of landholders,
(semi-)subsistence farmers and smallholder producers.
The growing concentration of farmland in Eastern Europe in
the hands of financially strong investors is encouraged by fertile
soil and cheap land prices, but it is reinforced by national and
international policies: both domestic governments and the
European Union (EU) support large-scale, export-oriented
agricultural projects. Moreover, many land-owners in Eastern
Europe have abandoned their plots due to a lack of income
opportunities and financial and technical resources, as well as
a lack of experience in agriculture. These abandoned plots have
fuelled demand from commercial farmers in search of land.
Despite this recent history, Eastern Europe today stands out as
a region where extraordinarily large areas are being acquired by
Sources: Eco Ruralis (2014); European Parliament (2015); OSW (2014);
Schivatcheva (2014); Spoor and Visser (2011); TNI (2013).
Case study provided by Anne Hoss and Afia Afenah, GIGA.
2.4.4. Tenure insecurity as a driver of land
acquisitions
An important question and issue for debate is whether and to
what extent security of land tenure can be considered a driver of
land acquisitions (Dwyer, 2013). It is possible that a high degree
of land tenure security is a factor that attracts investors, as
stable and clear conditions regarding tenure are important for
the long term? On the other hand, low levels of tenure security
could also encourage land acquisitions, as such conditions might
create opportunities for investors to acquire quick access to
large tracts of lands within legal systems that give little scope
for local populations to defend their own rights to land. Figure
13 shows that a number of countries that are significant targets
of land acquisitions (such as Cambodia, Ethiopia, Madagascar,
Laos and Ghana) are characterised by weak land tenure security,
despite agriculture being a very important sector in their national
economies. The figure implies a strong correlation between weak
tenure security and land acquisition, a correlation already shown
by others (Deininger, 2013; Anseeuw 2012). The implementation
of deals in countries where land tenure security is low could
also imply a difficult future for some of these projects, as conflict
over land might hinder the further development of some deals,
preventing the potential economic benefits of such investments
from being realised.
International Land Deals for Agriculture
» 20
Figure 13: Typology of land acquisitions: land tenure insecurity and agricultural GDP
16.6
SLE
10
5
50
Agriculture as % of GDP
ETH
40
Land Acquired
as percentage
of agricultural area
30
SDN
MOZ
IDN
10
ARG
URY
ZMB
RUS
LAO
GHA
NGA
GIN
20
MDG
PRY
MAR
UKR
ROU
BRA
COG
0
0
KHM
TZA
1
2
3
4
Land Tenure Insecurity
The size of the bubble represents the area of acquired land relative to the available agricultural area in any given country
Note: This figure shows 22 of the 25 countries with the largest areas of reported land acquisitions. Due to a lack of data, Papua New Guinea, South Sudan and
Liberia have been omitted. Also due to a lack of data, agriculture’s percentage of GDP for Zambia is not from 2014 but from 2013. See Figure 12 for the list of
names of countries corresponding to the ISO 3166-1 alpha-3 standard.
Data: Land Matrix 2016, World Bank 2014, FAO 2016, CEPIL 2012.
2.5. Synthesis
The Land Matrix currently reports on a total of 1,204 concluded
land acquisitions on 42.4 million hectares of land. It also takes
account of 212 intended deals, most of which have been
dormant for a number of years, and 97 failed deals that may
still continue to impact upon target regions. Three-quarters of
concluded deals are for less than 20,000 hectares, but there are
also some very large deals: 45 are larger than 200,000 hectares.
Agriculture continues to be the main intention recorded in the
Land Matrix, followed by forestry. Within agricultural intentions
(totalling 26 million hectares), food crops play the major role,
followed by agrofuels. There is also a huge and growing area
being used for unspecified agricultural deals. These are typically
crops that can be used for multiple purposes, such as oil palm.
This is reflected in the fact that 44% of all deals produce oil seeds,
though recently there has been a decline in the importance of
jatropha deals.
21 »
International Land Deals for Agriculture
The Land Matrix shows a growing trend of implementation: many
deals have concluded contracts and these are bringing land
under production at a growing rate. Usually, implementation is
quite rapid: most deals moving into the implementation stage do
so in less than three years.
Africa continues to be the most targeted region, followed by
Asia, Eastern Europe and the Americas. There are a number
of significant target countries in West and Eastern Africa.
Within countries, in drier areas acquisitions are particularly
concentrated along important rivers such as the Nile. The Land
Matrix also shows a wide diversity of countries affected; those
with a high Global Hunger Index, those where the agricultural
sector is a particularly important part of the economy and those
where tenure security is low are amongst those most strongly
targeted.
3 The Investors: Who, Where and Why?
This chapter looks in greater depth at who is involved in largescale land acquisitions. It answers questions such as where
investors come from, what types of investors are involved, what
their motives are and how they involve domestic partners.
It provides background on the investors who are driving the
findings presented in the previous chapter and gives insight into
their behaviour. This helps to provide a better understanding of
the impacts of large-scale land deals, which are analysed in more
detail in Chapter 5.
location(s) of stock exchange listings or main owners. Using the
location of a company’s HQ also partly circumvents the potential
for misinformation due to companies establishing subsidiaries in
tax havens (Cotula and Berger, 2015). Nevertheless, the opaque
structure of investor chains means that the Land Matrix is unable
to consistently identify the origin of each investor, with numerous
deals showing intermediary companies registered in tax havens
and not the origin of the capital.
A second issue arises when dealing with investments in which
multiple investors are engaged. For these cases, the full size
of the deal is attributed to the country of origin of each of the
international investors involved, to indicate the countries’ total
involvement in large-scale land acquisitions. This results in a
degree of double-counting and thus a higher number of deals
and a larger area than the total of unique deals. Overall, 77 deals
in the database have two or more investors, resulting in a total of
1,128 deals covering 28.5 million hectares (versus 1,004 unique
deals covering 26.7 million hectares).
3.1.Origin of investors
Determining the geographical origin of investors might be
straightforward in the case of governments and small private
firms. However, it is not so clear when it comes to larger
firms and in particular stock exchange-listed companies. The
ownership structures of many larger companies are difficult to
determine and a unique ‘origin’ for such firms is often impossible
to identify. The Land Matrix uses the location of an investor’s
headquarters to determine its country of origin, rather than the
Figure 14: Top 20 investor countries for concluded deals with agricultural intention
120
4 000 000
3 500 000
100
80
2 500 000
2 000 000
60
1 500 000
40
Number of Deals
Area (in hectares)
3 000 000
1 000 000
20
500 000
0
Land Area
Brazil
Cyprus
South Korea
South Africa
Jersey
Kazakhstan
Luxembourg
Canada
France
British Virgin Islands
Argentina
China
Hong Kong
India
Netherlands
Saudi Arabia
Singapore
UK
USA
Malaysia
0
Number of Deals
Source: Authors’ calculation based on Land Matrix data, April 2016.
International Land Deals for Agriculture
» 22
Figure 14 shows the top 20 countries for investor involvement
with regard to the area under contract, according to the Land
Matrix. It shows that investors are spread widely. Among Asian
investors, Malaysian companies stand out with engagement
in more than 3.7 million hectares. Investors from high-income
countries such as the USA and countries in Western Europe
are also prominent, with the United Kingdom the country with
the most deals. Overall, investors from high-income European
countries are involved in 315 concluded deals (31.4% of all such
deals) covering nearly 7.3 million hectares (27.2% of all land),
which makes this region the biggest investor region, followed by
South-East Asia. The remaining investors are based in the Middle
East, South America and the tax haven of the British Virgin
Islands. One investor from Kazakhstan is involved in a single very
large deal in neighbouring Russia. Combined, the top 20 investor
countries account for 67% of all concluded deals, covering over
81% of all the land under contract.
Over the past four years the top 10 investor countries have
changed, as can be seen from Table 10. The countries indicated
in green feature in both time periods (2000–2011 and 2012–
2016). The scale of investments from the USA has diminished,
while investments from tax haven countries such as Cyprus and
the British Virgin Islands have increased by comparison. Asian
investors have also become more dominant in recent years.
Table 10: Top 10 investor countries for contracts concluded in 2000–2011 and 2012–2016
2000–2016
Malaysia
TOTAL SIZE
(1 000 HECTARES)
2000–2016
3 737
2000–2011
United States
TOTAL SIZE
(1 000 HECTARES)
2000–2011
3 112
2012–2016
Malaysia
TOTAL SIZE
(1 000 HECTARES)
2012–2016
934
USA
3 314
Malaysia
2 803
Singapore
712
UK
1 838
UK
1 416
Cyprus
445
Singapore
1 679
Saudi Arabia
1 414
UK
422
Saudi Arabia
1 438
India
1 140
China
296
Netherlands
1 263
Hong Kong
1 082
Netherlands
264
1 000
India
1 245
Netherlands
Virgin Islands
204
Hong Kong
1 082
Singapore
967
USA
203
China
1 006
China
709
France
195
Argentina
602
South Africa
191
Argentina
744
Source: Authors’ calculation based on Land Matrix data, April 2016.
“Investors from the global South show a preference for investing in their own
region .”
3.2.Strong regional patterns
The Land Matrix applies a classification based on continents,
which are sub-divided into regions,15 thus allowing for analysis
of geographical patterns. This analysis shows that investors
from the global South show a preference for investing in their
own region (see Figure 15). The percentage of intra-regional
investment is highest for South American investors, who remain
within their own region in 85% of the deals they are involved in.
This figure is 67% for South-East Asian investors, while African
investors remain within their own region in 45% of deals.
A similar pattern can be seen for investors from high-income
countries. Of deals concluded by investors from Eastern Asia, 57%
are on the Asian continent, and nearly 50% of deals involving North
American investors are on the American continent. European
investors are mostly active in Africa. Investors from the Middle
East mostly acquire land in North and East Africa, and thus are still
relatively close geographically. The regional trend is similar when
looking at the area of deals, as illustrated in Figure 15.
15
The Land Matrix follows the United Nations’ regional classification (http://unstats.un.org/unsd/methods/m49/m49regin.htm), which is based on continents that
are sub-divided into regions. The continents, with their regions, are: Africa: Central (Middle), Eastern, Northern, Southern and Western; Americas: Caribbean, Central,
North and South; Asia: Central, Eastern, South, South-East and the Middle East (Western Asia); Europe: Eastern, Northern, Southern, Western; Oceania: Australia and
New Zealand, Melanesia.
23 »
International Land Deals for Agriculture
Figure 15: Geographical investment patterns by investor region for area under contract
7 000 000
Area (in hectares)
6 000 000
5 000 000
4 000 000
3 000 000
2 000 000
1 000 000
Western Europe
Western Asia
Western Africa
Southern Europe
Southern Asia
Southern Africa
South-Eastern Asia
South America
Northern Europe
Northern America
Northern Africa
Middle East
Middle Africa
Eastern Europe
Eastern Asia
Eastern Africa
Central Asia
Central America
Caribbean
Australia and New Zealand
0
Investor Region of Origin
Intercontinental
Continental
Regional
Source: Authors’ calculation based on Land Matrix data, April 2016.
In South-East Asia, intra-regional engagement is driven mainly
by Malaysian (and to a lesser extent Singaporean) palm oil
producers, who are expanding their production activities into
Indonesia. Vietnamese investors, mainly rubber producers,
are increasingly expanding their activities into neighbouring
Cambodia and Laos. On the other hand, Singaporean (mostly
leading investor Olam) and Indian companies are heavily involved
in Africa. Like Brautigam (2015), the Land Matrix does not show
any evidence of a large-scale “land grab” by Chinese investors in
Africa (see Box 6).
International Land Deals for Agriculture
» 24
Box 6: Chinese investment in African agriculture
China has had a longstanding and complex involvement in
African agriculture. Chinese engagement began in the 1960s
with the acquisition of large, previously state-owned farms. This
was followed by a push to set up demonstration farms and to
provide extension support for smallholders in the 1970s. In
the 1980s the focus shifted to making economic relations with
Africa more sustainable and mutually beneficial, through various
consolidation and experimentation projects. These projects led
to a substantial change in aid policy in 1995, with a bigger focus
on aid that would generate “mutual benefit”. By 2007 a significant
backlash had taken place, because large-scale Chinese land
acquisitions in Africa were perceived as land grabs intended to
produce crops for export back to China.
However, China’s involvement in African agriculture is
often overstated. African agriculture is not among China’s
geographical priorities. In fact, Land Matrix data shows that
most Chinese investors in Africa are individual farmers operating
on a relatively small scale, supplying mainly food crops to the
domestic market. A second category of involvement is through
agriculture technology demonstration centres, such as those
in South Africa (fisheries) and Uganda. These demonstration
centres, each covering less than 200 hectares, tend to function
as an anchor for commercially oriented investment. An intended
10,000-hectare rice farm in Cameroon (Case #1140) was started
on the site of a derelict aid project, but never moved beyond its
initial 100 hectares.
Another observation is the failure of large intended deals by
Chinese investors. For example, the Land Matrix records a project
by Kaidi Biomass Zambia Limited (Case #3739), a Chinese-owned
company that intended to acquire 300,000 hectares in Zambia
for biofuels, but in the end acquired only 4,000 hectares and
subsequently abandoned the project. A plan by another company,
ZTE, to obtain 100,000 hectares in the Democratic Republic of
Congo (DRC) also failed to get off the ground (Case #1984). The
company obtained only 865 hectares, and abandoned this land
after a few years. On the African continent, Chinese investors are
concentrating their efforts in other sectors, such as mining and
infrastructure development, rather than agriculture.
Sources: Brautigam (2015); Brautigam and Tang (2009); Jiang et al. (2016);
Gabas (2014).
Case study provided by Angela Harding, University of Pretoria, Regional Focal
Point Africa.
“Land acquisitions, project implementation and operation of activities often involve
complex investment chains that are characterised by multi-layered shareholding
and financing structures.”
In South America, intra-regional deals often involve large
Argentinian companies such as Cresud S.A., El Tejar and
Bellamar Estancias S.A., which have large investments in Brazil,
Uruguay, Paraguay and Bolivia. According to their websites, these
companies apply a business model focused on the acquisition of
large tracts of high-potential land, which are then used for grain
production (including soybeans and wheat) and rearing livestock
(cattle and sheep) (Cresud, 2014; El Tejar, 2014; Bellamar
Estancias SA, nd). North American investors also demonstrate a
preference for investment in South America.
3.3.Investor types and their networks
The Land Matrix distinguishes between several different types
of investor. Private companies are privately held by one or more
owners of private equity. Shares may be exchanged privately
but cannot be offered to the public, and companies are thus
not listed. Private companies vary greatly in size and scope,
ranging from relatively small investors who engage in a single
small project to large companies that have obtained multiple
land areas of considerable size. Stock exchange-listed companies
have shares that can be traded freely through an official stock
exchange. Some shares of a listed company might be reserved for
dedicated shareholders, such as a founding family. Investment
funds, which can also be publicly traded, are not included in
this category but have a separate category in the Land Matrix.
25 »
International Land Deals for Agriculture
The category of investment funds encompasses entities which
pool and invest funds provided by their clients. Some investment
funds are open to general clients, while others are owned solely
by one entity, e.g. a university, pension fund or government. Thus
investment funds can be used by both private investors and public
investors. If an investment fund is solely owned by a government,
it is included in the category of state-owned entities, which
includes all companies owned by different state institutions (e.g.
national or regional governments). Companies with a majority
government shareholding combined with other shareholders
are captured under semi state-owned companies in the Land
Matrix database. Only a few investors have been assigned this
category, however, and therefore in this report they have been
subsumed under state-owned entities. Further investor types
are individual entrepreneurs (unincorporated firms) and all other
types, such as NGOs, which are captured under Other.
It should be noted that land acquisitions, project implementation
and operation of activities often involve complex investment
chains that are characterised by multi-layered shareholding and
financing structures. Another reason for composite investment
chains is to benefit from preferential tax laws and possible
protection through investment treaties (Cotula and Blackmore,
2014). These structures often show low levels of transparency
and their components are thus difficult to trace.
Figure 16: Example of a multi-layered investment chain
Investment Fund (Singapore Government)
Investment Fund 01
(Singapore)
Investment Fund 02
(Singapore)
Singapore based Stock
Exchange-listed Company
Domestic
Government
Stock Exchange-listed
Company (Japan)
Investment Fund
(USA)
Others
Sale and Lease Back
(Plantation and Mill)
Previously 60%
Oil Palm Plantation and
Processing Factory
Land Lease
Previously 40%
Luxembourg-based
Investment Management
Firm
Source: Olam Group (2015 and 2016).
Figure 16 illustrates an example of the complexity of investor
chains involved in large-scale land acquisitions. In this case16,
the majority shareholder in an oil palm plantation is a subsidiary
of a stock exchange-listed company from Singapore, with the
remaining shares being held by the government of the target
country. Furthermore, a plethora of tertiary shareholders is
involved, including government-related investors, another stock
exchange-listed company and a number of investment funds
and banks. To make this case even more complex, the domestic
joint venture company has engaged an investment management
fund in a long-term lease of the land and a sale and lease-back
agreement for the plantation and processing mill. However,
financing partners such as banks and other lending institutions
that do not have direct equity and tertiary investors are not (as
yet) captured in the Land Matrix. Therefore, it is likely that the
role of stakeholders such as investment funds and pension
funds is underestimated in this analysis.
Though the Land Matrix does not currently fully reflect this multilevel ownership, it does allow for multiple owners. A distinction
is made between the primary investor (the company registered
in the target country) and secondary investors (the owners or
shareholders of this primary investor). A primary investor can
have a single investor behind it or multiple secondary investors.
In the latter case, the Land Matrix attributes the full size of the
deal to each of the shareholders as an indication of their total
involvement in large-scale land acquisitions, and thus doublecounts these cases, resulting in an overall total of 1,161 cases
versus 1,004 unique cases.
Table 11 lists the different investor types active in large-scale land
acquisitions in the global South for agricultural purposes. Private
companies are the main investors, followed by stock exchangelisted companies and investment funds. The key player is clearly
the private sector, and not “foreign” governments. A significant
number of land acquisitions involve investors for which the Land
Matrix has insufficient information.
Table 11: Land acquisitions by investor type
INVESTOR TYPE
AREA (1 000
HECTARES)
% OF TOTAL AREA
DEALS
% OF TOTAL DEALS
Private company
12 087
45%
407
41%
Stock exchange-listed company
8 485
32%
299
30%
Investment fund
2 521
9%
89
9%
State-owned entity
926
4%
62
6%
Individual entrepreneur
648
2%
31
3%
Other
74
0.3%
8
1%
3 202
12%
165
16%
No information
Note: N = 1,061
Source: Authors’ calculation based on Land Matrix data, April 2016.
16
Case #2236 in the Land Matrix.
International Land Deals for Agriculture
» 26
Table 12 shows investor types by region. This illustrates the
strong involvement of stock exchange-listed companies in
South-East Asia, indicating the importance of this investor type in
Asia. Private companies from Latin America, such as El Tejar, are
responsible for a large number of deals in the Americas.
Table 12: Land acquisitions by investor type and target region
INVESTOR TYPE
AFRICA
AMERICAS
ASIA
EUROPE
OCEANIA
Private company
4 571
2 139
1 247
2 224
1 907
Stock exchange-listed company
1 683
1 334
3 152
2 257
60
Investment fund
Area in 1 000 hectares
1 254
809
6
452
0
State-owned entity
422
190
277
36
0
Individual entrepreneur
223
314
6
106
0
Other
67
0
0
7
0
2 332
31
522
55
263
No information
Note: N = 819
Source: Authors’ calculation based on Land Matrix data, April 2016.
3.3.1. Private companies
Most concluded land acquisitions in the Land Matrix – over 40%
– and the largest share of acquired land area involve a private
company, around half of which are of European or South-East
Asian origin. Many private companies are involved in a small
number of deals, but private companies can be considerable in
size. An example of a large private company engaged in largescale land acquisitions is Louis Dreyfus Company, a leading
commodities trader and processor. This company has established
a subsidiary based in Argentina called Calyx Agro, which focuses
on agricultural land rental, acquisition and development across
South America (Louis Dreyfus Commodities, 2008). Additional
funding for these land-based activities was sourced from private
equity financing, resulting in investment companies obtaining
equity in Calyx Agro (Ibid.).
Box 7: The ABCD group in Latin America
The global market for grains and other agricultural products
is controlled by a small number of companies. Four of them –
Archer Daniels Midland (ADM), Bunge, Cargill and Louis Dreyfus
– are known as the ABCD group. These companies engage not
only in trading, but have recently begun a gradual diversification
process that includes the production and marketing of agroindustrial products. As a result, they now have a direct impact
along the entire value chain: from primary production through
trade to storage, distribution, processing and marketing across
numerous countries in South America. Based on the information
provided on corporate websites, Cargill operates in the most
countries, followed by Dreyfus, Bunge and ADM.
The companies of the ABCD group do not necessarily acquire
land to carry out their commercial activities. In fact, most of their
business is based on agreements with major regional producers.
Yet the direct acquisition of agricultural land still plays a role
in the business model of some of these companies. Access to
land for production purposes does not always imply a direct
purchase but can take different forms: contracts, agreements,
leases, production by third parties or any combination of these.
Even when land is effectively acquired, its actual use is often
exercised through financial subsidiaries or by leasing the land
to other business groups and investors. Acquisitions are heavily
dependent on the political, economic and legal framework of
each target country.
The websites of the ABCD companies report on their commercial
activities, but not much information is provided about the
27 »
International Land Deals for Agriculture
amount of land they actually own or the legal aspects of their
production systems. In fact, the Land Matrix database for Latin
America contains land deals for only three of these companies
(ADM, Cargill and Louis Dreyfus). ADM has acquired a relatively
small amount of land in Brazil for palm oil production in a
deal signed in 2012. Cargill’s acquisitions are concentrated in
Colombia (about 140,000 hectares in two land deals from 2010
and 2012). These deals were heavily criticised by the media
and by environmental and social organisations because they
were made through local subsidiaries in order to sidestep a law
that restricts the purchase of land by foreign companies. Louis
Dreyfus (through subsidiaries Calyx Agro and Louis Dreyfus
Company) has acquired land in Argentina, Brazil, Paraguay and
Uruguay (approximately 70,000 hectares in 12 deals signed
between 2005 and 2009). These deals are devoted mostly to
food crops and cattle ranching, sometimes in combination with
nature conservation projects.
Although the ABCD companies have acquired relatively small
amounts of agricultural land in Latin America, their increasing
control of the entire supply chain is likely to affect the food and
economic sovereignty of some countries in the region. Directly
or indirectly, these companies are also contributing to the
processes of deforestation and land use change taking place in a
number of Latin American countries.
Sources: Archer Daniel Midlands Company (2016); Bunge (2016); Cargill (2016);
Louis Dreyfus Company (2016)
Case study provided by Lucas Seghezzo and Cristian Venencia, FUNDAPAZ,
Regional Focal Point Latin America.
Private companies account for nearly half of the concluded deals
in Africa and the Americas contained in the Land Matrix (see
Table 12). Because of the importance of stock exchange-listed
companies in the South-East Asian palm oil sector, however,
their share is lower in Asia and Oceania.
All African private companies engage solely in Africa. Asian private
companies, on the other hand, often operate outside Asia, with
more deals concluded in Africa than in their own region. These
investors are mainly Indian companies investing in East Africa.
Malaysian private companies target land in their own region,
including Papua New Guinea. Intra-continental private company
investment in the Americas originates from the USA, with the
large agricultural processor Cargill among the investors.
3.3.2.
Stock exchange-listed companies
The Land Matrix data shows that the second largest investor type
engaged in large-scale land acquisitions is stock exchange-listed
companies. These companies often invest in multiple deals. The
largest investor globally is Olam, a Singapore-based company
active in both the production and trading of crops such as rice,
nuts, coffee and cotton and which recently has also expanded
into forestry activities. The Land Matrix has identified 20 deals
concluded by Olam, involving land acquisitions across Asia, Africa
and the Americas. The largest group of stock exchange-listed
companies is based in South and South-East Asia (see Box 8);
these companies are active in the region in oil palm production
on large-scale plantations, sometimes combined with rubber
production.
Box 8: South-East Asian dominance and expansion of oil palm plantations
Palm oil is widely used in everyday living, from household items
such as cooking oil and food, cleaning and cosmetic products
to industrial uses like lubricants and biofuels. Oil palm is a highyielding crop that compares favourably with other oil crops such
as rapeseed and soy. Demand for vegetable oils and biofuels has
pushed up demand for palm oil since the 1980s. This is reflected
in the Land Matrix, with oil palm being the single largest crop
mentioned in concluded land deals.
The main players in the oil palm sector are based in South-East
Asia. Several of these companies, such as Carson Cumberbatch,
M.P. Evans and Sime Darby, have a long history dating back
to the arrival of the British in East Asia, where they started
operating in the rubber and tea sectors. These companies
switched to oil palm plantations, mostly in Malaysia, in the 1960s.
Malaysian domestic entities, such as the Genting Group, TSH
Resources and the government-owned FELDA, also entered
the oil palm sector at that time. The production of palm oil by
these companies continues today, but the rise in demand has
encouraged them to increase their production and expand their
plantations overseas.
In South America, Cresud S.A., an Argentinian company,
exemplifies the trend of expansion into neighbouring countries
such as Brazil and Bolivia. This company follows a similar
business strategy to that of the privately owned Calyx Agro,
namely “acquisition, development and exploitation of agricultural
properties having attractive prospects for agricultural
production and/or value appreciation and the selective sale of
such properties where appreciation has been realized” (Cresud
S.A., 2014). Rather than acting independently, Cresud S.A. has
obtained a 39.76% share in BrasilAgro.
European stock exchange-listed investors in the Land Matrix
include Agrokultura AB17 (Sweden), Black Earth Farming (Jerseyregistered, with mostly Scandinavian-based institutional investor
shareholding) and DUI Holding A/S (Denmark), all of which
manage numerous farms in Eastern Europe (in Russia, Romania
and Ukraine).
For example, Felda Global Ventures Holdings Berhad (now stock
exchange-listed, with FELDA the major shareholder) currently
has activities in Indonesia, Thailand, Cambodia and Pakistan.
Sime Darby has expanded its operations to Indonesia, has
acquired plantations owned by New Britain Palm Oil Limited
(NBPOL) in Papua New Guinea and has established itself in Africa
with plantations in Liberia and Cameroon. Overall, the company
controls a land bank of almost 1 million hectares globally. Carson
Cumberbatch and M.P. Evans Group, which are not based in
Malaysia, have made strategic decisions to divest from the
country and move their focus to Indonesia. All these companies
have grown through mergers and acquisitions and operate
through a complex network of domestic subsidiaries, either with
full control or with majority or minority shareholdings. Overall,
the number of companies that have palm oil plantations in
Indonesia and Malaysia is not surprising; according to the World
Wide Fund for Nature (WWF), more than half of the world’s total
plantation area of palm oil is found in these two countries.
Sources: Carson Cumberbatch (n.d.); Cramb and Curry (2012); Felda Global
Ventures (nd); Genting Plantations (2014); M.P. Evans Group (2016); Nelson et
al. (2014); Sime Darby (2016); TSH (2016); WWF, 2004.
Case study provided by Lorraine Ablan, Asian Farmers Union, Regional Focal
Point Asia.
On the African continent the main investors besides Olam,
according to the Land Matrix, are Socfin and Amatheon Agri.
Socfin (Luxembourg) traces its origins back to 1890, and since
then it has established a large network of subsidiary companies
in which it holds majority or full ownership, through which it
manages rubber and oil palm plantations across Africa (Socfin,
2015) and which it continues to expand. A number of its
plantations were previously government-owned companies that
have been privatised. Since 2000, Socfin has acquired seven new
land areas, according to the Land Matrix. In contrast, Amatheon
Agri is a relatively new company from Germany, which focuses on
the development of large-scale commercial farming operations
in sub-Saharan Africa (Amatheon Agri, 2016). Since 2013, the
company has established operations in Zambia, Uganda and
Zimbabwe. Its recent land acquisitions have contributed to the
increasing focus of stock exchange-listed companies on food
crops, which has become relatively more significant since 2012.
17
Agrokultura AB, previously Alpcot Agro, was recently delisted from the Nasdaq First North stock exchange after a takeover by Steenord, an investment company
based in the British Virgin Islands (a tertiary investor). See:
http://news.cision.com/agrokultura/r/agrokultura-s-application-for-delisting-approved,c9700899; and http://www.businesswire.com/news/home/20141121005098/
en/Steenord-Corp.-Announces-Final-Outcome-Mandatory-Public.
International Land Deals for Agriculture
» 28
These examples illustrate the fact that stock exchange-listed
companies often engage in multiple land deals focusing on a
single geographic area.
3.3.3.
Investment funds
Investment funds engage with the agricultural sector in different
ways. As illustrated in the investment chain concept presented
by Cotula and Blackmore (2014), some investment funds opt to
obtain equity in agribusinesses, limiting the risk for the investor
as capital is not invested in fixed and socially sensitive land assets
(Anseeuw et al., 2011). This engagement, as a shareholder in an
agribusiness, is not visible in the Land Matrix. Other investment
funds instead choose to speculate directly on rising commodity
and/or land prices through land acquisition, which is recorded
in the Land Matrix. For example, the investment company
EmVest states on its website: “As sub-Saharan farming becomes
modernized, crop yields should start to rise and the value of land,
whether freehold or leasehold, will appreciate” (EmVest, 2012).
Investment funds following the strategy of direct land acquisition
have an interest in 8.9% of all land in concluded deals recorded
in the Land Matrix (see Table 11 above).
Figure 17: Regional trends of concluded deals by investment funds
900 000
Area (in hectares)
800 000
50
700 000
40
600 000
500 000
30
400 000
20
300 000
200 000
10
100 000
0
0
Africa
Intercontinental
Number of Deals
60
Americas
Continental
Asia
Regional
Europe
Total Number of Deals
Source: Authors’ calculation based on Land Matrix data, April 2016.
Whereas private and stock exchange-listed companies show
a relatively high degree of investment in their own regions,
this is less the case for investment funds (see Figure 17). Only
a few African- and European-based investment funds engage
in regional land acquisitions. Asia does not appear as either
an origin of or a target for investment funds, according to the
Land Matrix, with the few deals in which Asian investment funds
are involved targeting land outside the Asian continent. The
shareholding of Pacific Century Group (Hong Kong) in Calyx Agro
accounts for 10 of the 17 Asian deals in the Land Matrix. These
investments are, however, of a larger than average size, with the
area under contract nearly equalling that of the many investment
funds based in Europe.
3.3.4.
State-owned entities
State-owned entities are involved directly in large-scale land
acquisitions through four types of actor: fully state-owned
companies; semi state-owned companies whose equity is partly
owned by the state; investment vehicles with the state as the
sole stakeholder; and government departments themselves.
29 »
International Land Deals for Agriculture
The Land Matrix has a separate category for semi state-owned
companies, but this report combines this investor type with
the state-/government-owned category to capture all state
involvement. Overall, deals involving state-owned entities
account for 6.2% of concluded deals, covering 3.5% of the area
under contract in the Land Matrix (see Table 11 above).
One of the drivers for governments to acquire land is food security
(Luyt et al., 2013); governments with limited natural resources in
their own countries aim to achieve food security partly through
direct investment by the government-/state-owned entities. The
target government agrees to provide land for the government
searching for land, which then invites its domestic companies
to operate the land in the target country. (Both Jordan and
Egypt have tried to implement this strategy, although neither
has been successful.) Alternatively, governments operate
through sovereign wealth funds, in essence governmentowned investment funds, which engage directly in agricultural
deals with the aim of producing food for the investor country.
However, these intentions often remain on the drawing board,
with relatively few projects being implemented.
A second concern for governments appears to be providing
farming opportunities for domestic farmers, especially for
highly populated countries such as India and China. Examples
in the Land Matrix include Chinese provincial governments
that have secured land leases or have assisted in this process
in Kazakhstan, for Chinese citizens to farm. Similarly, the Indian
states of Punjab and Andhra Pradesh have outlined plans to
acquire land in order to send Indian farmers to Ghana and Kenya
respectively.18 This strategy is targeted more towards individual
farmers than large agri-businesses.
The highest number of concluded deals originates from stateowned entities in Vietnam and China. The Land Matrix captures
the largest number of deals for the Vietnam Rubber Group
(VRG), which controls 112,000 hectares of rubber plantations
extending over 17 concessions in Cambodia and Laos. The
company operates these concessions under a complex network
of local companies (Slocomb, 2011). Chinese investments are
more diverse, including the land in Kazakhstan acquired for
individual farmers but also state-owned companies engaging in
large commercial farming operations, such as sugar production
in Mali and the involvement of the agricultural department of
the Guangxi Zhuang Autonomous Region in a large-scale biofuel
deal in the Philippines.
3.3.5.
Beyond direct investment
Investment funds and governments play a relatively small role
as secondary investors in large-scale land acquisitions, but their
involvement stretches further through indirect engagement.
Investment funds play an important role in the financing of
stock exchange-listed companies. Pension funds, insurance
companies, endowments and universities are organisations
with large financial resources available. These institutions mostly
look to a large diversity of investments to spread their risk.
Agricultural investments are considered attractive for a number
of reasons: land values are likely to appreciate, land is a hedge
against inflation, it has a low correlation to other types of asset,
and a long-term upwards trend can be expected in food and
fuel prices (Luyt et al., 2013; TIAA Global Asset Management,
2016). Accordingly, pension funds from the USA, Scandinavia
and the Netherlands, among other countries, are shareholders
in numerous companies with deals recorded in the Land Matrix.
Another impact of investment funds is through debt financing.
In this scenario, the investment fund provides capital to an
agricultural operation without taking equity in it. Since the
Land Matrix captures only stakeholders with ownership, these
investment funds are not included in this analysis.
State-owned entities from high-income countries do not appear,
at first sight, to be engaged in large-scale land acquisitions.
Their role rather seems to lie in the financing of investors, for
example by holding equity in stock exchange-listed companies
or providing loan and/or grant financing to private companies.
Government policy can also play a stimulating role for businesses
to expand overseas. A clear example is the policy adopted by the
Saudi government to reduce primary agricultural activities in its
own country in order to preserve scarce water resources. As part
of this policy, the government has ordered a halt to domestic
wheat production as of 2016 (Blas, 2015). As a result, companies
such as Almarai, MIDROC and the Al Rajhi group have acquired
land outside Saudi Arabia to supply the Saudi market.
“Investment funds and governments play a relatively small role as secondary
investors in large-scale land acquisitions, but their involvement stretches further
through indirect engagement.”
3.4.Intention
The agricultural intentions of the top 10 investor countries are
illustrated in Figure 18. Most investors from these countries are
involved in food crop production, in line with the general findings
in Chapter 2. This is specifically the case for Saudi Arabian and
Argentinian investors. A few exceptions to investments for
food crops can be noted, however. Firstly, Malaysian investors
mostly target land for oil palm plantations, regularly combined
with rubber production, and hence they score high in the
18
categories of unspecified agriculture and non-food commodities.
Dutch investors engage in a relatively large number of projects
involving agrofuel crops, with UK investors also active in this
segment (although numerous projects have been abandoned by
investors, especially the larger deals). Lastly, livestock investors
seem to be concentrated in the USA, with little to no activity in
this sector by Asian investors.
Cases #202, #3361 and #4431.
International Land Deals for Agriculture
» 30
Figure 18: Intentions of top 10 investor countries
3 500 000
Area (in hectares)
3 000 000
2 500 000
2 000 000
1 500 000
1 000 000
500 000
Food
Unspecified
Non-food
Argentina
China
India
Hong Kong
Netherlands
Saudi Arabia
Singapore
UK
USA
Malaysia
0
Agrofuels
Livestock
Note: N (deals) = 546; N (intentions) = 820
Source: Authors’ calculation based on Land Matrix data, April 2016.
All investor types are involved in food production, as shown in
Figure 19. Investment funds in particular, and to a lesser extent
state-owned entities, appear to invest in land for food crops,
according to the data. This underlines the driver for governments
of ensuring food security for their own populations. As can be
expected from the previous finding on the large involvement
of stock exchange-listed companies in the oil palm sector, this
investor type targets a relatively large area for unspecified use
crops. Livestock projects are largely owned by private companies.
Figure 19: Intention of agricultural deals by investor type
12 000 000
Area (in hectares)
10 000 000
8 000 000
6 000 000
4 000 000
Food
Unspecified
Note: N (deals) = 1,004; N (intentions) = 1,493
Source: Authors’ calculation based on Land Matrix data, April 2016.
31 »
International Land Deals for Agriculture
Non-food
Agrofuels
No Information
Other
State-owned
entity’
Investment
Fund
Individual
Entrepreneur
Private
Company
0
Stock
exchangelisted company
2 000 000
Livestock
3.5.Partnerships with domestic
shareholders
In general, private companies engage in a large range of crops
but mostly produce sugar cane, rice, oil palm, rubber and
jatropha. Stock exchange-listed companies, on the other hand,
show a much larger preference for oil palm production, with
more than a third of the deals targeting this crop. Investment
funds, like private and public companies, are mostly engaged in
food production, predominantly soy and wheat but also corn,
rice and sugar. This type of investor is often engaged in projects
combining food production with extensive livestock activities.
Domestic investors such as private companies, individuals and
governments do not often participate in partnerships with
international investors. A total of just 155 concluded deals, or
15.4%, have shared equity between international and domestic
investors. This indicates that these investments have a low level
of inclusion of domestic stakeholders, limiting the impact of
foreign land acquisitions on local development (Chamberlain
and Anseeuw, 2016). These deals are slightly larger than average,
however, covering 18% of the area under contract (Table 13).
Note that deals made exclusively by domestic investors are not
included in these 155 agreements, as such deals are not within
the scope of this report (see Chapter 1).
Table 13: Shared equity with domestic investor by target region
TARGET REGION
SIZE
(1 000 HECTARES)
% OF SIZE OF AREA IN
TARGET REGION
DEALS
% OF DEALS IN
TARGET REGION
Africa
2 610
26%
86
20%
Americas
1 459
32%
30
21%
Asia
557
11%
33
11%
Europe
192
4%
6
6%
Oceania
Total
0
0%
0
0%
4 818
18%
155
15%
Source: Authors’ calculation based on Land Matrix data, April 2016.
Investors most often team up with domestic partners when they
invest in Africa or the Americas, where just over 20% of deals
have shared equity with a stakeholder from the target country
(Table 13). This percentage is much lower for Europe. Domestic
partners in Oceania do not hold equity in any of the deals in their
own countries.
Table 14: Investor types engaged with a domestic partner
INVESTOR TYPE WITH
DOMESTIC PARTNER
SIZE
(1 000 HECTARES)
% OF TOTAL SIZE
INVESTOR TYPE
DEALS
% OF ALL DEALS
INVESTOR TYPE
Private company
1 892
16
59
15%
Stock exchange-listed
company
1 554
18%
50
17%
Investment fund
365
15%
9
10%
State-owned entity
192
20%
12
21%
Individual entrepreneur
42
7%
7
23%
Other
3
3%
1
13%
827
26%
25
15%
No information
Source: Authors’ calculation based on Land Matrix data, April 2016.
Table 14 illustrates that, based on the data in the Land Matrix,
individual entrepreneurs are the most likely type of investor
to partner with a domestic partner. State-owned entities also
engage with a domestic partner in more than a fifth of their
large-scale overseas land acquisitions. Investment funds tend to
operate without a domestic partner.
International Land Deals for Agriculture
» 32
Table 15: Domestic shareholders by investor type
DOMESTIC INVESTOR
TYPE
Stock exchange-listed
company
AREA (1 000
HECTARES)
DEALS
1 442
20
State-owned entity
900
36
Other
612
4
Private company
562
43
Individual entrepreneur
455
19
Investment fund
64
5
No information
Total
784
28
4 818
155
“Investors most often team up with
domestic partners when they invest in
Africa or the Americas, where just over
20% of deals have shared equity with
a stakeholder from the target country.”
Source: Authors’ calculation based on Land Matrix data, April 2016
Most domestic partners are private companies, which
corresponds with the dominant type of international investor
(Table 15). Domestic stock exchange-listed companies are
involved in a particularly large total land area. Involvement of
domestic state-owned entities mostly occurs when foreign
investors target African countries.
Table 16: Intention of deals with domestic stakeholders
INTENTION
AREA (1 000
HECTARES)
% OF AREA WITH
DOMESTIC PARTNER
DEALS
INTENTION AS % OF
DEALS
Agrofuels
1 702
34%
42
19%
Food crops
1 103
13%
95
17%
Livestock
190
10%
17
13%
Non-food
337
15%
21
9%
Agriculture unspecified
758
14%
41
16%
Note: N (deals) = 155; N (intentions) = 268.
Source: Authors’ calculation based on Land Matrix data, April 2016.
Deals with a domestic partner are relatively more focused on
agrofuel production, as illustrated by the large area under
contract for this intention (Table 16). More than a third of the
area for agrofuel crops is in deals where a domestic partner has
part-ownership. Fuel production projects with domestic investor
involvement are considerably larger than agrofuel deals with no
domestic partner, as can be deduced from the larger percentage
of area (33.6%) compared with the percentage of deals (19%).
The opposite is the case for food crops. Regarding the relatively
high number of fuel deals, it is important to remember that a
number of crops, mainly sugar and oil palm, are used for both
food and fuel. Thus the primary intention might be food, with fuel
production a secondary application. Deals for these crops are
counted under both food and fuel production. Domestic partners
are less involved with non-food agricultural commodities and
livestock activities.
US companies has recently slowed down. Investors from the UK
account for the largest number of land deals.
3.6.Synthesis
The intentions of the main players vary considerably. While most
are involved in food production, some investor countries show a
stronger preference for other crops, especially agrofuels. Domestic
partners have shareholdings in a relatively small number of deals.
Quite often, however, land acquisitions with a domestic partner
are for fuel crops on a larger than average scale.
The leading investor countries are in South-East Asia, with Malaysia
the largest. Investors from this region are mostly stock exchangelisted companies that are targeting Indonesia and Papua New
Guinea for palm oil production. The USA remains the second
largest investor country, though the pace of land acquisitions by
33 »
International Land Deals for Agriculture
Private companies are the leading investor type, followed by stock
exchange-listed companies and investment companies. The key
player is clearly the private sector, and not “foreign” state-owned
entities. Private sector investors expand either horizontally or
vertically, or speculate on increasing land and commodity prices.
Investment funds and state-owned entities are relatively small
players when looking at direct land acquisitions. However, these
investor types often form part of opaque investment chains, and
thus their impact is likely to be bigger than what is reflected in the
Land Matrix. Governments furthermore serve as a driver through
policies that enable investors from their own countries to expand
overseas or that create an attractive environment for foreign
investors to invest in their domestic agricultural sectors.
4. What Type of Land is Targeted by Land Deals?
What type of land is sought after by investors? As well as the
countries targeted, it is very important to investigate what type
of land is acquired within each country. The local context is
vital regarding the impacts of a land deal. Central determinants
include environmental conditions, land cover, whether the
location is highly populated and accessible and whether it is
already being used for farming or other purposes.
4.1.Tropical savannah and tropical
rainforest are the most targeted
climatic zones
In Chapter 2 a global map representing areas with a high
concentration of land deals was presented (Figure 10). We have
further examined areas with high densities of land acquisitions
according to climatic zones.19 This analysis draws on 943
concluded agricultural deals out of the total 1,204 in the Land
Matrix that contain geospatial information at different levels of
accuracy.
40
40
35
35
30
30
25
25
20
20
15
15
10
10
% Area in Target Countries
% of Deals
Figure 20: Share of land acquisitions in different Köppen–Geiger climate classes in target countries
5
5
0
% of deals in climate class
Other
Arid Hot Desert
(BWh)
Arid Steppe Hot
(Bsh)
Temperature,
Dry Winter,
Hot Summer (Cwa)
Cold, No Dry
Season, Warn
Summer (Dfo)
Temperature,
No Dry Season,
Hot Summer (Cfa)
Tropical Monsoon
(Am)
Tropical Rainforest
(Af)
Tropical Savannah
(Aw)
0
% area climate class in target countries
Note: Compiled in April 2016 using GLOBE incidence of land deals (Ellis, 2012) according to the different climatic zones (orange) and their respective over- or
under-representation (green) in terms of the share of each type of zone for target countries. For example, tropical savannah represents 16% of the land area
in target countries, but the sample shows that 37% of land deals are in this climate class.
We use climate zones according to the Köppen–Geiger climate classification (Kottek et al., 2006), to determine the climate zones in which land acquisitions
most frequently take place. This system divides the earth into five main climate zones (Group A (tropical climates), group B (dry climates), group C (temperate
climates), group D ( Continental climates), and group E ( Polar climates), each consisting of several sub-types. We display these sub-types here and give the
corresponding code in brackets.
Source: Land Matrix, April 2016.
Figure 20 represents the incidence of land deals according to
the different climatic zones (orange) and their respective overor under-representation (green) in terms of the share of each
for target countries. The analysis shows that both tropical
savannah and tropical rainforest climate zones are clearly overrepresented in the global sample in terms of land deals. This
results mainly from the trend in Asia, where these climate zones
are preferred targets for oil palm plantations, due to the very
high productivity that can be attained.
19
In order to give more insight we also present sub-regional maps,
one for West and Central Africa and one for East Africa (Figures
21 and 22), showing the localisation of deals in these regions. It
can be seen that in both regions deals focus on tropical savannah
and tropical monsoon areas. Crops such as oil palm or sugar
cane are the most prominent crops in these tropical areas. In
East Africa, temperate climates are also heavily targeted.
For methodological considerations on this point, refer to Eckert et al. (2016).
International Land Deals for Agriculture
» 34
Figure 21: West and Central Africa: Spatial distribution according to climate zones of land deals contained in the Land Matrix
Land Deal Site
Af: Tropical Rainforest
Am: Tropical Monsoon
Aw: Tropical Savannah
BWh: Arid Desert Hot
BSh: Arid Steppe Hot
Source: Land Matrix, April 2016. Köppen–Geiger climate zones according to Kottek et al. (2006).
Arid zones account for only a low share of sites relative to the
land area in the targeted countries. Land deals for agricultural
purposes mostly occur in arid climates only if a possible source
of irrigation is available. This can also be observed on a global
scale (see Figure 10). The under-representation of arid zones at
global level can obviously be understood by the lack of water
to sustain large-scale production, which points to the key role
of water resources in the land acquisition process (Breu et al.,
2016).
Figure 22: East Africa: Spatial distribution according to climate zones of land deals contained in the Land Matrix
Land Deal Site
Af: Tropical Rainforest
Am: Tropical Monsoon
Aw: Tropical Savannah
BWh: Arid Desert Hot
BWk: Arid Desert Cold
BSh: Arid Steppe Hot
Csa: Temperature, Dry Summer, Hot Summer
Csb: Temperature, Dry Summer, Warm Summer
Cwa: Temperature, Dry Winter, Hot Summer
Cwb: Temperature, Dry Winter, Warm Summer
Cfa: Temperature, No dry season, Hot Summer
Cfa: Temperature, No dry season, Warm Summer
Source: Land Matrix, April 2016. Köppen–Geiger climate zones according to Kottek et al. (2006).
35 »
International Land Deals for Agriculture
Tropical rainforest is under-represented in West and Central
Africa as a target zone for agricultural land acquisitions (as can
be read from Figure 21). In Central Africa, tropical forests are
mainly targeted for forest concessions rather than agricultural
crops such as oil palm.20 This can be explained by political
and economic factors (e.g. access to markets, infrastructure,
economic environment, preference for regional engagement
by Asian investors), which lead to different patterns of land
acquisition.
4.2.Former land use and land cover
Once land deals begin to be implemented, we witness changes
in land use and land cover, with the previous land use and
cover changing to cropland for commercial agriculture. Areas
undergoing land use and land cover changes not only lose their
economic and cultural functions for local populations, but also
lose many of their previous environmental functions; these are
among the impacts of land deals discussed in Chapter 5.
A limited number of delas (287 deals) in the Land Matrix provide
information on the type of former land cover on the land
acquired. Three land cover types are reported most frequently:
cropland, forest land and marginal land (see Figure 23).
“Croplands are by far the most frequently reported former land cover type, with
more than half of all deals implemented (at least partially) on former cropland,
rather than on uncultivated land.”
Figure 23: Primary land cover types targeted by land deals
58%
Cropland
27%
Forestland
5%
10%
Shrub-/Grassland
Marginal Land
Note: Individual deals list up to three different former land covers. The Land Matrix does not provide information on the share of area for each type of former
land cover; hence, for this analysis, we have divided the area under contract and attributed equal shares to each former land cover. N (deals) = 287, N (former
land cover) = 428.
Source: Authors’ calculation based on Land Matrix data, April 2016.
Croplands are by far the most frequently reported former land
cover type, with more than half of all deals implemented (at
least partially) on former cropland, rather than on uncultivated
land. Earlier analysis conducted by Messerli et al. (2014) on the
context of land deals (albeit with a different methodology and
sample of deals) also points to a high proportion of cropland
being affected. Some 27% of deals take place on former forest
land; deals targeting rubber or oil palm cultivation very often fall
into this category. Marginal land is the third important category
of former land cover recorded in the Land Matrix (10% of deals).
However, the term “marginal” does not specify what type of land
this actually is, and in many cases it may include land that is used
by pastoralists (Messerli et al., 2014).
The type of former land cover is extremely important for
many reasons. The loss of cropland to a large investor has a
direct impact on the food security and livelihood strategies of
the smallholder farmers affected. The loss of forests means
a loss of biodiversity and carbon sequestration, which has
global consequences. Furthermore, forests serve as sources
of firewood, timber and other resources for local communities.
Land considered to be “marginal” often serves as a grazing area
and is important to rural communities and indigenous peoples.
These points are discussed further below.
20
This report focuses only on land deals for agricultural purposes, which do not include forestry concessions. Forestry deals are therefore not depicted on the map,
but they are included in the Land Matrix database.
International Land Deals for Agriculture
» 36
Table 17 shows the distribution of former land use expressed
as a percentage of the size of land currently under contract for
commercial farming operations. Across all regions, almost threequarters of the acquired area was formerly used for commercial
(43%) and smallholder (31%) agriculture. The share of these
two categories is particularly high in Eastern Europe (96%), but
also in Asia and Latin America, with over 75%. In Oceania, and
to a lesser extent in Africa, many new commercial farms have
been set up on former forestry land. Land used by pastoralists
and conservation areas seem to be less frequently targeted by
foreign investors (5%).
Table 17 : Regional distribution of former land use
Africa
Latin America
Asia
Eastern
Europe
Oceania
Total
Commercial (large-scale)
agriculture
23%
47%
44%
71%
19%
43%
Smallholder agriculture
36%
28%
34%
25%
29%
31%
Pastoralists
5%
7%
3%
4%
0%
5%
Forestry
29%
11%
11%
0%
53%
16%
Conservation
7%
6%
8%
0%
0%
5%
Note: Individual deals list up to four different former land uses. The Land Matrix does not provide information on the share of area for each type of former land use;
hence, for this analysis, we have divided the area under contract and attributed equal shares to each former land use. N (deals) = 298, N (former land use) = 398.
Source: Authors’ calculation based on Land Matrix data, April 2016.
4.3.Socio-ecological contexts of acquired
land
In order to further investigate local contexts, more detailed
research was conducted by Messerli et al. (2014) on a sub-sample
of land deals contained in the Land Matrix. Their analysis used
information on 139 intended and concluded agricultural deals
for which more precise geospatial information was available and
analysed these deals based on land cover, population density
and accessibility of the target area.
Population density: Analysis of the local context revealed
on average a considerable population density – 81 people per
square kilometre in contexts dominated by croplands (Messerli
et al., 2014). When relating this to the overall size of land
acquisitions reported in the Land Matrix, we need to consider
that the data refers to the context in which land deals take place
and not the land actually acquired. Nevertheless, Messerli et al.
(2014) extrapolated that, worldwide, some 33 million people may
potentially be affected (directly or indirectly) by the concluded
deals presently recorded in the Land Matrix. Illustrative of the
difficulty inherent in this estimation is that the best land is
frequently subject to large-scale land acquisition even in sparsely
populated areas, such as semi-arid zones, and this is land where
herders bring their animals during the dry season and periods of
drought. As a result, they may be forced to relocate to even more
marginal land in search of water and fodder and hence be driven
deeper into poverty.
Accessibility: Land deals are often seen within a perspective of
improving access in remote areas. However, in reality, in many
cases investors follow the opportunities (i.e. lower cost of access)
created by public infrastructure. Over 50% of the 139 deals
analysed are in relatively accessible areas, less than six hours’
travel from a city of 50,000 or more people; in Africa, nearly 80%
of the deals are within this range. About 30% are within 3–4
hours of the nearest city (Messerli et al., 2014).
Combining this data with data on land cover in the target areas,
Messerli et al. postulated that large-scale land acquisitions
and their impacts could be clustered into three distinct socioecological patterns. Each of these three patterns involves a
distinct type of competition over land between its various
functions and related stakeholder claims. The patterns of land
acquisitions targeting different types of local context and the
significance of these can be described as follows (based on
Messerli et al, 2014).
Densely populated and easily accessible areas with
cropland mosaics: This pattern applies to about one-third of
land deals in the sample; this finding supports criticism of the
assumption that land deals target mostly “idle” or “unused”
land (Borras et al., 2011). This type of local context is often
characterised by strong competition for land and concerns
that it is often already being used by smallholder farmers. Such
competition is likely to result in deals having negative impacts
on livelihoods and on gender equality, with evictions, loss of
customary land rights and changed property regimes. Case study
research related to this pattern shows that negative impacts
generally outweigh the benefits of such land deals.
Largely remote and sparsely populated forestland: This pattern
again applies to one-third of the land deals studied, but it
contrasts with the less competitive situation found in densely
“Over 50% of the 139 deals analysed are in relatively accessible areas, less than
six hours’ travel from a city of 50,000 or more people; in Africa, nearly 80% of the
deals are within this range.”
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International Land Deals for Agriculture
populated and easily accessible croplands. Case studies have
described two relevant processes that relate to this pattern.
First, research has shown that land acquisition is often used as a
means of securing access to and control over natural resources
such as trees and water (Borras and Franco, 2012). Control over
forests is an important incentive for investors, as income from
logging activities required for land clearance may compensate
for initial capital investments. Moreover, forest-related land
use systems such as shifting cultivation are vulnerable to rapid
transformation, as they are widely viewed as backward and
economically unproductive (Heinimann et al., 2013; Hurni et al.,
2013; van Vliet et al., 2012). Second, studies have found neoliberal
tendencies in initiatives aimed at conserving natural resources.
Conservation agencies which acquire land for purposes of
environmental protection or carbon sequestration have been
accused of contributing to “green grabbing”, as their initiatives
deprive local people of access to land (Messerli et al. 2014).
Moderately accessible and moderately populated shrubor grassland: About one-quarter of the analysed land deals
were found to occur in contexts where shrublands or grasslands
dominate. In many cases, this type of land is used as rangeland
under pastoral systems, but it also includes fallow land. It is often
managed as a common pool resource. From a purely economic
perspective, such land may appear to be under-used and thus
might seem to have considerable potential for development.
However, “pastoralist communities are often marginalised and
ignored in decision-making processes, and at the same time they
are particularly vulnerable to loss of land rights and to disregard
of their specific claims on socio-ecological functions of land.
Furthermore, environmental risks related to water stress and
desertification are considerable” (Messerli et al., 2014). This type
of land is often termed “marginal” by outside observers and also
within the Land Matrix dataset (see Figure 23), although it is often
very important for local livelihoods. The issue of the impacts of
land acquistions is further explored in Chapter 5.
4.4.Synthesis
Beyond the question of which countries are the preferred targets
of land acquisitions, it is also important to take into account the
different socio-ecological contexts in which such deals take place.
According to findings based on the Land Matrix, many land deals
target relatively well accessible areas, due to the importance
of good access to inputs and market destinations. For more
than half of the area targeted, the previous land cover was
already cropland. Population densities in these areas have been
estimated to be relatively high, leading to competition and even
conflict over scarce land and water resources. However, land
deals also take place on forested land and on marginal land and
shrub- and grassland used by pastoralists. Although population
densities are often lower in such cases, many communities are
affected through the loss of access to these areas.
Areas of tropical rainforest and tropical savannah are often
acquired, very often for the establishement of palm oil and
rubber plantations, especially in Asia. This causes large-scale
environmental and social impacts.
International Land Deals for Agriculture
» 38
5. Impacts of Large-Scale Agricultural
Land Acquisitions
This chapter looks at the impacts that large-scale land acquisitions
have on target countries and affected communities. The extent
of these impacts depends upon the institutional, ecological
and socio-economic contexts of transactions (discussed in the
previous chapter) and on the governance strategies used by
multiple actors. Box 9 identifies recurrent patterns from case
studies found in scientific peer-reviewed articles and provides
insights into the implications of large-scale agricultural land
transactions.
Positive impacts generally include jobs and access to
infrastructure. On the negative side, loss of access to land and
natural resources, increased conflict over livelihoods and greater
inequality are frequently highlighted in case studies and scientific
literature, to which the Land Matrix also refers. As discussed in
Chapter 2, many deals are still only in the start-up phase and
it is not yet possible to provide a full picture of their long-term
impacts. The impacts of investments in the production phase
are often not yet visible either, and can only be inferred through
comparison with investments that have been established for a
longer period.
Box 9: Meta-analysis reveals patterns of livelihood impacts
The implications of large-scale land acquisitions for the livelihoods
of people living in the target regions differ substantially across
cases, affected people and contexts. However, despite such
great diversity, a meta-analysis of 44 scientific studies covering
66 cases in 21 countries in Africa, Asia, Central and Southern
America and Eastern Europe identifies certain patterns of
livelihood implications.
many land investments become more mature over the coming
years. An array of identifiable risk factors makes the occurrence
of such adverse processes more likely. The most notable
risk factors include asymmetric participation by land users in
economic and political decision-making, an illusion of lands
being marginal, unrealistic visions of progressive change and
pre-existing inequalities in affected communities.
The most frequently identified adverse livelihood impacts are
loss of access to land and natural resources (24%), increased
conflict over livelihoods (18%) and greater inequality in local
communities (9%). The underlying processes that generate
such adverse impacts include enclosure of livelihood assets,
elite capture, selective marginalisation and polarisation of
development discourses. In situations involving enclosure, local
land users lose their land rights without being able to sufficiently
rebuild their livelihoods. With elite capture, local or state elites
are able to extract disproportionally high shares of benefits
from land acquisitions, while land users bear the bulk of the
socio-economic and ecological costs. In situations of selective
marginalisation, a group of former land users experiences a
reduction in their livelihood assets while other land users, other
than the elite, are not affected or even benefit.
The most frequently reported positive livelihood impacts relate to
the creation of benefits for land users at a household level (35%),
in particular through stable, decent employment and access to
infrastructure. The creation of benefit is more likely if land users
desire to escape traditional societal structures, have de facto
power of veto against a land deal or have low opportunity costs
related to losing land rights. Pathways of adaptation and coexistence (11% of cases) have become possible, if households
and communities retain land rights or access new market niches.
Communities have been able to organise collective resistance
(19%) either to fight off investor land claims in the first place
or to regain rights and livelihoods after a deal has taken place
through political and social unrest. Participation of community
representatives in negotiations with investors is sometimes
reported (19%) to enable land rights protection or compensation,
but in other cases this has given rise to undesirable processes of
elite capture and selective marginalisation.
Together, these four processes account for 88% of the diagnoses
given in the 44 case studies. Less frequently observed are
processes of competitive exclusion, agribusiness failure and
transient job creation, though these may occur more often as
Source: Oberlack et al. (2016).
Meta-analysis of case studies provided by Christoph Oberlack, CDE.
“The impacts of large-scale agricultural investments not only depend on the local
context but also differ across the project cycle: a mature farm has a different effect
from a project in the start-up phase.”
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International Land Deals for Agriculture
The impacts of large-scale agricultural investments not only
depend on the local context but also differ across the project
cycle: a mature farm has a different effect from a project in
the start-up phase. This also explains the difficulty of assessing
the impacts of land acquisitions, as many projects are still very
new (see Chapter 2). Accordingly, we have looked into the
implications across time and distinguished – in accordance
with the Land Matrix’s variable “implementation status” – three
different phases of the project cycle: a) land acquisitions (project
not started), b) the start-up phase and c) operational projects (in
production). It is important to remember that deals that have
failed can continue to have implications for local communities.
5.1.Acquisition of land: little consultation
and frequent rejection of deals by
communities
Land acquisition has one direct and immediate effect: ownership
of the land changes hands. The former ownership of land
according to reports in the Land Matrix (336 deals for which
information is available) is attributed to private largescale
farmers (32%), communities (28%), the state (25%) and private
smallholders (15%).21
Figure 24: Former land ownership (% of area)
32%
Private (large-scale)
28%
Community
25%
State
15%
Private (small-scale)
Note: Individual deals list up to three different former owners. The Land Matrix does not provide information on the share of area for each type of former
ownership; hence, for this analysis, we have divided the area under contract and attributed equal shares to each former land owner. N (deals) = 336, N (former
land owner) = 386.
Source: Authors’ calculation based on Land Matrix data, April 2016.
In many regions and countries state ownership co-exists with
customary land tenure, either individually or community-based.
Hence for many land deals, state ownership could still imply that
land is owned traditionally by communities. Important questions
in such cases include the following. Through which process has
the ownership or right of use been transferred to the investor in
such cases? Was this process based on free, prior and informed
consent (FPIC)? Were customary land rights respected, especially
if formal ownership was in the hands of the state? With whom
have community land rights been negotiated and did all sections
of local society have a voice in this process? How were the rights
of marginalised social groups respected?
In lease agreements this change in ownership is temporary
– but, as discussed in Section 2.1, leases tend to have a long
duration, in many cases up to 99 years. A more structural change
in ownership takes place in the case of direct purchase but also
in situations where communal land tenure is transferred to state
land in order for the national government to enter into a lease
agreement with a foreign investor. This happens, for example,
in Zambia, where conversion from communal land to state land
is non-reversible and hence has a long-term impact on the local
community, regardless of the duration of the lease agreement
(Nolte, 2014).
A crucial aspect in the process of acquiring land is consultation
with communities, particularly in cases where land used or
owned by communities is affected. Analysis of the data shows
that in 41% of cases there is no consultation (see Figure 25). In
about 14% of cases a FPIC process has been conducted, while
in 43% a limited form of consultation has taken place. The Land
Matrix also contains information on how communities have
reacted to a project. In 60% of concluded deals, in a sub-set of
180 cases, it records rejection and in 17% consent, while in the
21
Deals where the former land-owner is a private large scale-farmer do not meet the criteria for inclusion in the Land Matrix. However, some deals also involve land
that was originally community- or smallholder-owned but has since been resold by one private actor to another. In this case the deal appears under the category
of private ownership, and is still of interest to the Land Matrix as the land has been lost by the local community. There are also deals where commercial agriculture
was part of the former use but the land was also used for other purposes. In some cases, the Land Matrix criteria may not have been met, but such cases still need
to be followed up and verified.
International Land Deals for Agriculture
» 40
remaining 23% there were mixed reactions. To find out whether
community reactions actually have an impact on negotiations,
we also looked into failed deals. Of 97 deals that have failed,
only eight included information on community reaction: seven of
these (in seven different countries) reported rejection and one
mixed reactions. In rare cases, community reaction may affect
the negotiations; however, given that 60% of the 180 concluded
deals analysed triggered a negative response, in most cases it
evidently has little impact. It is important to note that the fact
that some form of consultation has taken place is not sufficient in
itself to judge the quality of the consultation process, as this can
be selective and can bypass important groups that are affected
by a land deal.
Figure 25: Community consultation
80
70
70
66
Number of Deals
60
50
40
30
22
20
10
3
5
0
Free Prior and
Informed Consent
Limited
Consultation
Not Consulted
Other
Note: N = 161
Source: Authors’ calculation based on Land Matrix data, April 2016.
A change in ownership through a land acquisition usually leads
to a) some form of payment, b) a halt to former activities on
the land, and c) potential displacements which may involve
compensation payments.
Payments for acquired land depend largely on the national
context. There can be one-off payments, regular rent fees or
non-monetary payments, often within the scope of corporate
social responsibility (CSR). Many governments wish to promote
investments in the agricultural sector and request development
of the land instead of monetary payments (for example, see
Bottazzi et al., 2016 for the case of Sierra Leone). In other cases,
investors are seen as an engine for development and are meant
to contribute to community infrastructure, and consequently
are exempt from monetary payments. Furthermore, payment
structures can be complex, with revenue flowing to both the
local community and the national government.
The diversity of payment models, as well as their sensitivity,
explains why it is so difficult for a database like the Land Matrix to
store information on this issue. The LM database has information
on purchase prices (per hectare)22 for only 28 concluded
international agricultural land deals. These include deals in Brazil
(€221 to €2,626 per hectare) and five deals in Romania (€100 to
€3,200 per hectare). In 61 cases, the Land Matrix has information
on lease prices of concluded international deals (per hectare),
including 21 cases in Ethiopia (under €1 to €119 per hectare, with
most deals between €3 and €10), five cases in Liberia (€1–4) and
four deals in Sierra Leone (€1–10). Although data is limited, this
shows the diversity of payments within and between countries;
this might well be linked to different land values, reflecting factors
such as production potential, scarcity of land, tenure security
and market access, as well as other conditions specified in the
contract (e.g. tax exemptions, duration of the deal).
22
To make the purchase and lease prices comparable, we have converted all currencies to euros at the exchange rate on 1 July of the year in question (using historical
exchange rates: http://www.xe.com). These calculations do not take account of inflation.
41 »
International Land Deals for Agriculture
Acquisitions usually result in former land use activities ceasing
and hence lead to a loss of economic and cultural functions.
For instance, if land was formerly used for smallholder farming,
smallholders might lose access to their fields, with consequences
for food security (see Box 12). The acquisition of land may
also lead to the displacement of communities, including both
voluntary resettlements and forced evictions.
Looking at former land-owners (Figure 24), almost half of the area
targeted (43%) was formerly owned by communities, including
indigenous peoples, or smallholder farmers, which means that
acquisitions are likely to lead to voluntary or forced displacements.
Information on displacements is scarce in the Land Matrix, with
information for just 89 cases. Of these, 57 mention physical
displacement, with some specifying the number of individuals
(23 cases) or households/families (21 cases). These deals show
that projects where displacement occurs generally involve a
large number of people: only three of them displaced fewer than
500 individuals and eight fewer than 100 families. Seven deals
are reported to have displaced more than 10,000 individuals and
five deals have displaced more than 500 families. A further 21
deals mention people living in the area of the project, which has
the potential for future displacements. The remaining 11 deals
that do not mention actual or potential physical displacement
do mention the loss of farming land and/or the loss of access to
land for hunting, grazing or other activities.
Compensation is sometimes paid to people or communities who
have lost their access to land. Whether a company as the new
land-owner or the government as the former land-owner has a
legal obligation to compensate depends on national legislation
and on the land tenure status of former land users. Sometimes
the benefits of investments, such as jobs and infrastructure, are
also perceived and announced as a form of compensation (see
the section below on “Operational projects” and Figure 27 on
such benefits). The Land Matrix contains 101 agricultural deals
where compensation is reported; however, in only about onethird of these cases have promises materialised at least partly,
in one-third of cases compensation has never been promised or
has not been received, and in the remainder the status is unclear
(Figure 26).
Figure 26: Status of compensation offered
30
29
Number of Deals
25
20
19
15
13
15
13
12
10
5
0
Promised, but
not received
Promised, partly
received
Promised,
received
Promised,
status unclear
No
compensation
promised
No information
/ unclear
Note: N = 101, information entered as free text in the Land Matrix data was categorised according to these six categories.
Source: Authors’ calculation based on Land Matrix data, April 2016.
Few cases provide more detailed insights into actual
compensation measures, which may include resettlement
sites, alternative land or monetary compensation. The basis for
monetary compensation ranges from payments per home or
family to payments per area or productive entity (e.g. trees, area
of planted crops). Purely monetary compensation is reported in
about one-third of cases where some information is available.
See Box 10 as an illustration of the land acquisition phase
where an investor’s plans are met with resistance by the local
population.
International Land Deals for Agriculture
» 42
Box 10: Resistance to land deals – the case of Senhuile in Senegal
Senhuile (Case #3433) is a joint venture between Tampieri
Financial Group (Italy) and Senethanol (Senegal). The company
currently has 10,000 hectares under contract in the area of
Ndiael. It originally had two leases in different locations, but the
Government of Senegal repossessed parts of the land in 2016. A
first lease of 20,000 hectares was granted in 2012 for 50 years,
of which 10,000 hectares was repossessed; and a subsequent
lease in 2015 for an additional 5,000 hectares in Fass Ngom
was revoked. The company uses the land it still holds for the
production of biofuels and food crops.
From the beginning, there has been heavy resistance to the
project. Initially, land was allocated to the company in Fanaye.
After large-scale protests – in which people lost their lives – the
project was relocated to its current sites around the villages of
Gnit, Ross Bethio and Fass. The allocated land, community and
state-owned, was previously used by local communities for
smallholder agriculture. The communities were only consulted
during the social impact assessment in 2013, when the land had
already been acquired.
In response to the lease, the communities have created an
association called “Collectif de Défense des Intérêts du Ndiael”,
which comprises 37 villages and a number of CSOs. In February
5.2.Start-up phase: temporary employment
creation and infrastructure
development
In the start-up phase, considerable creation of employment can
be expected, but only for a short period of time: land preparation
and setting up the farm are merely a transition period. Farm
development often entails infrastructure developments
that might also benefit local communities: for instance, the
construction and improvement of roads or connection to the
2014, villagers even travelled to Europe, to the offices of Tampieri,
to protest against the project. In total, around 9,000 community
members from 40 villages have been affected by the project.
No-one has been displaced, but the local community has lost
access to grazing land, to land for cultivation and the collection
of timber, and to water collection points. Villagers living in close
proximity to the project are under constant threat of eviction by
company representatives and local police.
In an effort to improve working relations between the company
and the community, an agreement was signed in 2014 outlining
the compensation and benefits that communities would receive.
This stipulates that Senhuile will provide 0.3 hectares of land per
family for grazing and cultivation; so far, 189 hectares have been
allocated to families. The memorandum also promises other
community benefits, such as the construction of classrooms and
the creation of community gardens for women, but these have
not yet materialised. On the other hand, Senhuile has delivered
fodder to affected community members to compensate for the
loss of grazing.
Sources: Franchi and Manes (2012); ActionAid (2014a and 2014b); ActionAid
(2016).
Case study provided by Angela Harding, University of Pretoria, Africa Regional
Focal Point.
electricity grid. Infrastructure developments also continue
throughout the operational phase. Both employment creation
and infrastructure development in the transition phase are
difficult to track in the Land Matrix data currently,23 but Box 11
illustrates this stage.
Box 11: Setting up a farm – Dominion Farms Ltd in Kenya
Dominion Farms Ltd (Case #1374) is a private US investment
located in Kenya’s Siaya and Bondo districts. In 2003 Dominion
signed a 25-year lease agreement for 6,900 hectares of land. The
company mainly produces rice, which is sold across the country
under the “Prime Harvest” brand, but also fish and bananas.
During the start-up stage, Dominion was welcomed to the area
with some enthusiasm. People could see how the new farm
affected their lives: roads were paved and electricity came to the
area because of it. During this initial phase, the investor drained
swampland, which made land available for agriculture – though
this also raised environmental concerns (see Box 13).
Most importantly, employment was abundant in the first few
months of the project; for example, people were employed to
prepare the land and chase away birds. However, when the
farm became more and more mechanised, these unskilled jobs
vanished – and with it the initial enthusiasm.
Source: Nolte and Väth (2015).
Case study provided by Kerstin Nolte, GIGA.
“In the start-up phase, considerable creation of employment can be expected, but
only for a short period of time: land preparation and setting up the farm are merely
a transition period.”
In the next version of the LM Global Observatory, the history of deals will be improved so that the database can store more time-related information and hence
track the development of job creation over time – if this information is available.
23
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International Land Deals for Agriculture
5.3.Operational projects: socio-economic
and ecological implications
Finally, the effects of an operational project can only be observed
in the case of mature projects. This explains why we still know
so little about these effects: many projects have not yet, or
have only just, reached the production stage (see Table 7).
However, as discussed in Chapter 2, deals are now increasingly
being implemented and we therefore expect that the impacts
of operational projects will be felt more in the target countries
over the coming years. Box 12 and 13 provide examples of the
implications of land deals that have been in operation for a
number of years. While the focus of this report is clearly on land
acquisitions for agriculture, in certain countries acquisitions for
other purposes such as mining play an important role. Mining
deals24 equally have important socio-economic and ecological
impacts. Box 14 provides an example of one such case and
its impacts in Mongolia’s Umnugobi province. The literature
identifies a number of transmission channels through which
operational land deals may impact directly upon the livelihoods
of local communities: in particular, infrastructure development,
employment generation, access to agricultural markets and
spillovers to local communities, but also adverse environmental,
social and economic effects (see, for example, Kleemann and
Thiele, 2015; World Bank, 2010; and also Box 9).
Box 12: Bioenergy project fails to deliver promised benefits
Addax Bioenergy Ltd (Case #1798) is a Swiss-based company
producing sugar cane in Sierra Leone on about 10,000 hectares
of land leased from the Temne ethnic group. An interdisciplinary
group of researchers from the Institute of Social Anthropology
and the Centre for Development and Environment (CDE), both
at the University of Bern, and the National Research Programme
(NRP 68) investigated how this project has changed access to
land and natural resources and the effects this has had on
livelihoods, food security and ecosystem functions. Due to the
significant financial contributions of national and multilateral
development agencies, the project established by Addax
Bioenergy Sierra Leone (ABSL) had to comply with a series of
investment standards, including those of the Roundtable on
Sustainable Biomaterials (RSB), and is therefore considered by
many to be a “best practice” example.
The main findings of the research team were as follows.
• The project’s large-scale monoculture has destroyed a highly
diverse cultural landscape, significantly changing the quality
of and access to land, water and veldt products, especially
for more marginal groups i.e. women, youth, tenants and
migrants. Many land users have been excluded from
accessing common pool resources, losing previous access
rights based on common property institutions. Overall, on
average the amount of land used per family for agriculture
in the project area is 73% smaller than outside the project
area (2.53 hectares compared with 9.16 hectares). Those
with no land of their own are more seriously affected by this
reduction in land than land-owners (-70% compared with
-50%).
• Payments for the leasing of land are low and have been
made only to land-owners, who make up about 50% of
the people living from agriculture. This compensation has
exacerbated existing tendencies towards elite capture of
the project’s economic benefits, further intensifying tensions
and conflicts among different groups within Temne society.
24
•
•
•
•
Total monetary income in the project area is only 18% higher
than outside the project area. Meanwhile, expenditure on
food in the investigated area has risen by 16% compared
with the area outside, meaning that practically all of the
additional income in the project area must be used to pay
for increased expenditure on food.
As a consequence, families in the region studied are more
susceptible to the effects of fluctuation and crises outside
of agriculture. The serious effects of such dependency have
already been experienced twice in quick succession by
people living in the study area: first the Ebola epidemic, and
then the cessation of ethanol production following ABSL’s
decision to sell its project.
In the beginning, local people welcomed the project as they
anticipated it would bring development and salaried work
to the area. As these expectations failed to materialise as
expected, different responses were triggered. Local elites
as well as the younger generation have activated both old
and new ways of resistance, resorting to old institutions of
resistance (secret societies) and to a combination of old
and new tenure institutions and international legal rights
with the aid of a local NGO to win back control over the
commons.
During the implementation phase Addax created over 2,500
mostly part-time jobs, but the bulk of these have been
phased out since it ended operations in August 2015.
Even though this project has provided some economic benefits,
it has also caused severe negative impacts and the pre-existing
local context has led to an unequal distribution of these
negative impacts, mainly affecting groups that were already
disadvantaged.
Sources: Botazzi et al. (2016); Käser (2014); Lustenberger (2015); Marfurt
(2016); Marfurt et al. (2016); Rist et al. (2016).
Box provided by Tobias Haller, Stephan Rist, Fabian Käser, Franziska Marfurt
(all University of Bern).
Mining deals will soon be made public on the Land Matrix.
International Land Deals for Agriculture
» 44
Box 13: Rice project falls short of development potential
Thirteen years after it was first implemented, the impacts of a
large-scale land investment can be observed in the Yala Swamp
in Kenya, a wetland region of more than 200 sq km (Case #1374).
Kenya’s underlying legal pluralism, dating back to colonial times,
provided a legal basis for a US investor, Dominion Farms Ltd, to
lease 6,900 hectares of swampland, primarily to produce rice.
The lease was agreed with local county councils in the name of
development, and as such was welcomed by political leaders.
However, discussions about how best to implement the project
have been stifled by arguments associated with ethnicity, with
groups such as the Kikuya being accused of preventing Luo
groups in the region from achieving industrial development and
modernity.
Four major issues have arisen from this development:
1. Reclamation of the swampland has had an impact on the
resilience of local communities. This becomes evident when
comparing the population who benefited directly from the
swamp’s resources (15,000–35,000 people) with those who
benefit directly from employment created by the investment
(200 permanent jobs, 400 casuals). The loss of a major
livelihood source, combined with a lack of employment
opportunities, means that the diversification of livelihood
strategies is limited.
2. An area of 450 acres of land was allocated as compensation
for the loss of resources. However, after Dominion Farms
drained the land, local institutions were ignored and no
further steps were taken to distribute the land to local
3.
4.
people. Consequently, some wealthy community members,
using paid labour, rushed to clear this land in order to lease
it themselves. Vulnerable people, including elderly women
and poorer peasant farmers, were unable to continue using
the land as they had before.
Of the 6,900 hectares leased by Dominion Farms, only 40%
has so far been put into use. The remaining 60% still lies
fallow and to some part has been appropriated by local
people for grazing and cultivation. This has resulted in the
investor criminalising local people by calling in police to evict
them.
Dominion Farms has increasingly been collaborating with
local NGOs working for environmental protection of the Yala
Swamp. However, as these projects largely fail to take into
account the views of local stakeholders, the people affected
fear losing more land as a result of conservation efforts and
wildlife protection measures.
Considering these issues and the fact that the rice produced by
Dominion Farms is not consumed locally, this project appears
to have had a number of negative effects. Local people want
more labour opportunities and stronger integration of local
stakeholders, including the community’s knowledge, experience
and way of living, in order for more people to benefit from the
investment.
Source: Based on field research in Kenya, 2014.
Box provided by Elisabeth Schubinger and Anna von Sury (both Institute of
Social Anthropology, University of Bern).
Box 14: Mitigating the impacts of mining operations
Oyu Tolgoi LLC, a mining company joint-owned by the Mongolian
government and international investors, operates a mine about
600km south of the country’s capital Ulaanbaatar in Umnugobi
province, where it has extracted copper and gold since 2009
(Case #4569). The zone used by the company for mining and
related infrastructure overlaps with the Small Gobi Strictly
Protected Area (SPA), which is rich in biodiversity. People in this
water-scarce desert area rely on traditional nomadic animal
husbandry for their livelihoods.
The company’s operations have had a considerable impact on
this fragile environment. For instance, the only river in the region,
the Undai, was diverted to supply water to the mine. Sixteen
herder families with 61 members have been displaced and have
had to give up their pastureland. An additional 80 households,
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International Land Deals for Agriculture
with 365 members, have not been physically displaced but
have also lost their pastureland. However, all the families have
received in-kind compensation from the mining company and
alternative grazing areas have been identified.
The company tries to mitigate adverse effects by investing in
sustainable development projects, including education and
training for herders – for instance, two kindergartens have
been built in Dalanzadgad. The company’s activities have also
provided an economic stimulus, first and foremost by creating
employment. Its workforce is 95% composed of Mongolian
nationals, of whom 21.7% are from the South Gobi community
(as of December 2015).
Sources: Oyu Tolgoi (2016); Nutag Partners LLC (2015).
Box provided by Hijaba Ykhanbai, Jasil.
5.3.1. Development of social and community
infrastructure
Besides the infrastructure development accompanying the
establishment of farms, as mentioned in the section above on
the start-up phase and in Box 11, some investors deliberately
invest in community infrastructure – often as a way of community
compensation or CSR. As Figure 27 shows, community
benefits take a number of forms. Most frequently mentioned
are investments in education through the establishment of
schools (96) and health facilities (76) such as clinics, followed by
productive infrastructure such as irrigation, tractors or
machinery (51), roads (44), capacity-building (44) and financial
support through loans (16). However, Land Matrix data does
not permit any assessment of the percentage of cases where
these investments are actually implemented or to what level the
expectations of local people are met.
Figure 27: Community benefits
120
Number of deals
100
96
76
80
60
51
44
44
39
40
16
20
0
Education
Health
Productive
Infrastructure
Roads
Capacity
Building
Financial
Support
Other
Type of benefit
Note: N = 148 (multiple answers possible)
Source: Authors’ calculation based on Land Matrix data, April 2016.
5.3.2.
Employment generation
One of the most frequently cited benefits from large-scale
land acquisitions is the net creation of employment. If a newly
established farm creates wage employment in a rural region,
this is supposed to increase the incomes and social security of
employees, leading to increased welfare.
Unfortunately, data on employment is still difficult to obtain. This
is not surprising, given the seasonal fluctuation in labour demand
in agriculture. Drawing on a limited sample of 127 cases, we
looked at labour intensities, i.e. employment per 1,000 hectares
under operation (Figure 28). Labour intensities tend to be very
low – in a large number of cases, below 50 workers per 1,000
hectares. These low figures suggest capital-intensive production
and, with it, a limited capacity to absorb rural employment.
Ideally, our sample would be sufficiently large for us to compare
labour intensities across crops, as some crops are more labourintensive than others. For instance, the three cases with the
highest labour intensities include tea and grape production, while
among the lowest labour intensities are many cases of grains
and cereals, where typically production is highly mechanised.
"Labour intensities tend to be very low and suggest capital-intensive production
with a limited capacity to absorb rural employment."
International Land Deals for Agriculture
» 46
Figure 28: Labour intensities in the Land Matrix
50
47
45
40
Number of deals
35
30
25
20
20
15
15
14
15
14
10
2
5
0
Fewer than
50
50 to 150
51 to 250
251 to 500
5001 to
1000
1001 to
2500
More than
2500
Employment per 1,000 hectares
Note: N = 127. Employment per 1,000 hectares under operation. Where the area under operation is not given, we use a share of the area under contract.
The share is determined by all deals that have both the area under contract and the area under operation.
Source: Authors’ calculation based on Land Matrix data, April 2016.
Box 15 provides more insights into the potential of land
acquisitions for creating employment, pointing to an immediate
net employment loss but calling for more research, including into
medium- and long-term effects in order to complete the picture.
Box 15: Large-scale land acquisitions – employment generators or job killers?
To understand the immediate impacts of large-scale land
acquisitions on the rural labour market, three key determinants
must be taken into account. First, the former land use indicates
if and to what extent employment is crowded out; in particular,
smallholder farmers are likely to lose their livelihoods if a
commercial farm is set up on former smallholder land. Second,
the type of crop cultivated defines labour input, since labour
requirements differ greatly between crops. While the cultivation
of some crops can be performed largely with machinery (e.g.
corn, wheat, soybeans), the scope to substitute capital for
labour is quite limited for other crops (e.g. tea, coffee, bananas).
Accordingly, crops can be classified as either labour- or capitalintensive. Third, the production model applied might mitigate
crowding out, for instance by using contract farming schemes.
An analysis of these factors based on Land Matrix data shows
that the crowding out of smallholder farmers is a serious
concern across all regions: over one-third of the land acquired
was formerly cultivated by smallholder farmers (see also Table
17). Moreover, capital-intensive crops are three times more
commonly cultivated compared with their labour-intensive
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International Land Deals for Agriculture
counterparts. Lastly, contract farming schemes are only partly
able to mitigate crowding out, since they are applied on only
about two out of every 10 hectares of land affected.
The large-scale crowding out of smallholders, in combination
with the strong preference of commercial farmers for capitalintensive crops and the relatively low prevalence of contract
farming schemes, points to a net employment loss. In different
countries, this loss is estimated to range between 28% (Tanzania)
and 75% (Kenya) compared with smallholder farming. Although
these losses have a big impact in the immediate proximity of
the investment site, on the national level they reflect on average
less than 1% of overall employment in agriculture. However,
this is only half the story. To assess the macroeconomic impact
of large-scale investments further research is needed, taking
into account other factors such as price and wage effects and
sectoral linkages. These medium- and long-term effects might
trigger a change in the sectoral composition of an economy and
absorb the released labour.
Source: Nolte and Ostermeier (2016).
Box provided by Martin Ostermeier, GIGA.
5.3.3.
Access to agricultural markets and
spillovers
A commercial farm in a rural area also has non-immediate impacts
in terms of transforming the sector, such as linkages to other
industries and formalisation of employment. While an accurate
assessment of these processes would need to go beyond the
Land Matrix, 434 deals confirm that in-country processing of
products is taking place or is intended. This shows that land
acquisitions have further effects on the domestic economy.
season and in return sell their produce to a large-scale farm,
with the harvest paying off the loan at the end of the season.
The pros and cons of contract farming are heavily debated
in the available literature, but it is said to be a success in the
context of land acquisitions (De Schutter, 2011). One aspect that
fuels the debate is the fact that contract farming often favours
smallholders who are already better off (Bellemare, 2012).
Many farms are located in close proximity to smallholder
farmers and hence better access to markets and spillovers in
agricultural techniques can be expected. As seen in Figure 27,
access to productive infrastructure is one of the community
benefits commonly generated by large-scale investments.
Generally speaking, access to markets and spillovers depends
largely on the business model in use: the more inclusive it is,
the higher the chances of positive spillovers (FAO, 2013). The
Land Matrix data gives some insights into contract farming,
which is considered an inclusive business model (Chamberlain
and Anseeuw, forthcoming). In these arrangements, smallholder
farmers generally receive inputs on loan at the beginning of the
In the Land Matrix data, 159 deals are reported to use some
form of contract farming (47% of deals that have information on
this issue) (Figure 29). Most contract farming takes place on areas
not leased by the investor, but on land owned by outgrowers
(101 cases). The remaining 38 cases have implemented a tenant
farming model, where smallholder farmers produce for a largescale investor on land that belongs to the investor. A typical crop
produced under a tenant farming arrangement is oil palm, with
15 cases (eight of them in Indonesia). The largest shares of deals
that involve contract farming are in Africa (113) and Asia (34).
Figure 29: Regional distribution of contract farming
Number of Deals
120
100
80
60
40
20
0
Africa
Americas
On the Lease
Asia
Not on the Lease
Europe
Oceania
No further Information
Note: N = 159
Source: Authors’ calculation based on Land Matrix data, April 2016.
“There is potential for outgrower schemes to include and potentially benefit
local communities. Nevertheless, these cases illustrate that setting up outgrower
schemes in remote areas also involves challenges.”
International Land Deals for Agriculture
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Box 16: Outgrower schemes in Zambia
Amatheon Agri Ltd and Chobe Agrivision are two large investors
in Zambia who are currently setting up large outgrower
schemes. Amatheon, located in Mumbwa district, launched its
outgrower programme in April 2013 with the goal of involving
8,500 smallholder farmers in growing maize and soybeans (Case
#3783). Chobe has an operational scheme in Mpongwe (Case
#3125) and is currently setting up an outgrower scheme near its
Mkushi operations (Case #2053), with the aim of involving 5,000
to 10,000 farmers in growing maize and wheat.
Both investors stress that their outgrower schemes on the one
hand serve the purpose of including the local population, but
on the other are also beneficial to their own businesses, as they
will increase market share and company-owned mills can run at
full capacity. Schemes are group-based and provide farmers with
inputs and training on conservation farming, access to credit and
The number of outgrower farmers in these schemes ranges
between 10 and 35,000, with a mean of 4,468 and a median
of 1,250 (based on 34 observations for which information is
available).
Currently, an analysis of the impacts of outgrower farming
models is beyond the scope of the Land Matrix data, as more
detailed information over a longer period of time is needed. Box
16 provides case study insights into two farming operations in
Zambia that are currently setting up large outgrower schemes.
These cases show that there is potential for outgrower
schemes to include and potentially benefit local communities.
Nevertheless, these cases illustrate that setting up outgrower
schemes in remote areas also involves challenges.
5.3.4.
Environmental effects
In terms of environmental effects, as well as the context and
the former land use, much depends on the mode of production
implemented in individual large-scale land deals and any
mitigation measures taken. For instance, production based on
a guaranteed market. A number of local partners are involved in
setting up the schemes, for instance through training or financial
services.
Smallholder farmers involved in these schemes report the
benefits of training, improved availability of inputs and better
access to markets and credit. However, one of the main
challenges in the field is to explain the complex schemes to
local smallholders who in some cases are suspicious, as the
way the schemes work remains unclear to them. This highlights
the degree of involvement that is required from investors to
make contract farming work: it demands careful planning and
continuous engagement with local communities.
Source: Nolte and Subakanya (2016).
Box provided by Kerstin Nolte, GIGA.
a monoculture with heavy use of pesticides is likely to have a
more adverse environmental impact than conservation farming.
The introduction of agro-industrial production methods on
large areas, using high-yielding crop varieties, will entail the
displacement and further decline of local agro-biodiversity.
However, such changes also need to be put into perspective
against possible negative environmental effects of previous land
use systems, such as possible soil nutrient mining, extensive
slash-and-burn systems of farming or over-use of natural
resources by impoverished smallholders or pastoralists.
The Land Matrix does not cover environmental information in
detail, due to the difficulty and complexity of reporting such data
in a meaningful way. However, there is rich case study evidence:
for instance, Box 17 on a case in Salta province in Argentina
stresses the far-reaching environmental and social implications
of agricultural expansion. This case study illustrates how
governments may adapt their policies to address environmental
problems, although it also shows that these are not without
ambiguity.
Box 17: Environmental concerns and silvopastoral systems in Salta, Argentina
The production of raw materials and commodities for export is
the main driver of agricultural expansion in Latin America, and it
is almost always associated with large land transactions. Much
of this expansion has caused deforestation of native forests and
other environmental problems (such as erosion, soil salinisation,
loss of biodiversity and an increase in CO2 emissions) and social
unrest (displacement of rural populations, unemployment, loss
of traditional livelihoods).
In the province of Salta in northwestern Argentina, a national
law passed at the end of 2007 classifies native forests into three
categories: I (high conservation value), II (medium conservation
value) and III (low conservation value). Deforestation for
productive activities can only be authorised in category III forest
land.
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International Land Deals for Agriculture
The possibility of allowing different types of silvopastoral
production systems (combining forestry and the grazing of
animals) in category II forests is currently under discussion. This
would enable an increase in agricultural production without
engaging in the political and social debates that would be
generated by a new land use planning process. Case #4974
in the Land Matrix, a 9,700-hectare farm purchased in 2004,
is currently trialling a silvopastoral production system. In this
case, livestock for export is raised on land subject to forest
management practices that avoid total deforestation. According
to preliminary results, the production of beef is virtually the
same as in conventional farming systems. However, additional
studies are needed to conclusively prove the feasibility and
environmental sustainability of this production system.
A major problem is that the government has not allocated
sufficient funds to strengthen environmental control agencies. In
this context, authorising silvopastoral systems on category II land
without any assurances that strict monitoring will be enforced
could simply lead to hidden deforestation.
The government’s policy is ambiguous: while on the one hand
meetings are held with multiple stakeholders to discuss the
technical aspects and benefits of silvopastoral systems, on the
One variable that is captured is information on the source of
water extraction. For the 102 deals that have this information,
the great majority use surface water, e.g. rivers and lakes (78).
Sixteen deals use only ground water, and eight use ground and
surface water (Figure 30). This by itself does not signify an overuse of resources, but it could be a pointer towards increased
competition for water with other uses. Chapter 2 illustrated a
other hand intensive farming and monocultures continue to
be encouraged, even on state-owned land. For instance, deals
#1060 (228,000 hectares) and #4130 (228,000 hectares) are
clear examples of public land concessions for intensive soybean
production.
Source: Based on field research conducted in Salta province since 2007. For
further contextual information, see Seghezzo et al. (2011).
Box provided by Cristian Venencia, Lucas Seghezzo, Martín Simón and Gabriel
Seghezzo, FUNDAPAZ, Regional Focal Point Latin America.
concentration of land deals along major rivers, indicating further
evidence of land acquisitions impacting on water availability for
other users. Access to water has also been highlighted in the
literature as a possible driver of land acquisitions (Mehta et al.,
2012); however, this is still debated (see also Box 18, which uses
a sample of 475 deals from the Land Matrix to study the effects
of land acquisitions on water resources).
Figure 30: Sources of water extraction
90
80
78
Number of deals
70
60
50
40
30
16
20
8
10
0
Surface water
Ground water
Both ground and
surface water
Source of water extraction
Note: N = 98
Source: Authors’ calculation based on Land Matrix data, April 2016.
International Land Deals for Agriculture
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Box 18: Effects of land acquisitions on water resources
Insights from reports and various case studies suggest that
foreign investment in agricultural land is often motivated by the
appropriation of water resources attached to that land, a notion
commonly also referred to as “water grabbing”. According to a
further hypothesis, large-scale land acquisitions thereby serve
the goal of relieving pressure on domestic water resources in
investor countries by means of a “virtual water trade”.
To test the “virtual water trade” hypothesis, we analysed 475 land
acquisitions in the Land Matrix database. This analysis shows
that, at a global level, implementation of the land acquisitions
in the sample would result in increased water savings based on
virtual water trade. The realisation of these land acquisitions in
host countries would save 23.4% of crop water consumption
compared with the same crops being produced domestically in
the investor countries. However, in host countries the intensity
of water use would increase, in a phenomenon that could be
described as “water grabbing”. Nearly two-thirds of crop water
consumption by land acquisition projects would be concentrated
in just 10 out of 59 host countries. In at least 21 host countries,
including 15 sub-Saharan states, crop water consumption per
hectare would increase compared with their current average
agricultural water consumption. Further, through statistical
analysis it can be shown that host countries with abundant water
resources are not preferred per se to arid or semi-arid countries
as target areas of land acquisition.
Looking at investor countries, we see that a small number are
responsible for a large share of water consumption related to
land acquisitions. As few as six out of 54 investor countries –
Saudi Arabia, China, Malaysia, the United States, India and
Brazil – account for more than half of the total of this kind of
water consumption in host countries. We also show that land
acquisitions by 20 investor countries would increase host
countries’ average domestic crop water consumption if they
were implemented, indicating that investors in land abroad
might indeed be motivated by the aim of reducing pressure
on their own water resources. The group of countries that
are disproportionately externalising crop water consumption
includes big investors such as the USA, Saudi Arabia, Singapore
and Japan. At the same time, a number of countries that are
often suspected of acquiring land abroad to relieve pressure on
their domestic water resources – such as China, India and all the
Gulf States except Saudi Arabia – tend to invest in agricultural
activities abroad that are less water-intensive on average than
their own domestic production. Thus, the repeatedly voiced
hypothesis that investor countries’ investments in land abroad
are motivated primarily by relieving pressure on domestic water
resources appears to have little basis in reality.
Source: Breu et al. (2016).
Box provided by Thomas Breu, CDE.
5.4.Synthesis
This section has shown that large-scale land acquisitions can
have far-reaching implications, both positive and negative, for
target regions. Specific effects are very diverse, depending on
individual deals and the specific contexts in which they take place
– and they differ across time.
Third, employment is an important determinant of whether
projects have beneficial results. The data held in the Land Matrix
is not yet sufficient to determine the extent of labour creation
through land acquisitions, but first evidence suggests relatively
low labour intensities in projects that are up and running.
Based on our analysis, we can draw some overall conclusions.
First, the land targeted by land deals has often been used before,
mainly for agricultural activities, pastoralism and forestry. As land
acquisitions only rarely take place on idle land, they can potentially
have serious implications for people living on the land or using it.
Acquisitions are frequently marked by limited consultation, and
communities are increasingly opposing projects.
Fourth, contract farming models are an option for including
local smallholders. Land Matrix data shows that a substantial
share of deals employ contract farming systems. However, such
schemes are not automatically beneficial to participants (or to
non-participants), and a high degree of involvement by investors
is necessary to make the model work.
Second, in the start-up phase and continuing once the project
begins operations, infrastructural benefits are reported, with
investments in community infrastructure, such as health and
education facilities.
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International Land Deals for Agriculture
Fifth, it is important to gain a better understanding of the tradeoffs between socio-economic and environmental aims. In-depth
case studies have shown the complexity and importance of local
contextual factors. The Land Matrix data can serve as a starting
point to support further impact studies.
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Notes
International Land Deals for Agriculture
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The support of the BMZ (German Federal Ministry for Economic Cooperation and Development), the European Commission
(administered through Expertise France), the French Ministry of Foreign Affairs, the Swiss Agency for Cooperation and Development
(SDC) and the Swiss National Science Foundation is greatly appreciated.
The LMI Partners and Regional Focal Points are:
www.landmatrix.org

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